import cobra
#!wget http://www.ebi.ac.uk/biomodels-main/download?mid=MODEL1603150001 -O recon2.2.xml
Recon2 = cobra.io.read_sbml_model("Models/recon2.2.xml")
#Recon204 = cobra.io.load_matlab_model("Models/Recon2.v04.mat")
Recon2.reactions.OIVD3m.gene_reaction_rule='HGNC:2698 and HGNC:987 and HGNC:986 and HGNC:2898 or HGNC:2698 and HGNC:2898 and HGNC:987 and HGNC:986'
Recon2.reactions.OIVD1m.gene_reaction_rule='HGNC:2698 and HGNC:987 and HGNC:986 and HGNC:2898 or HGNC:2698 and HGNC:2898 and HGNC:987 and HGNC:986'
Recon2.reactions.OIVD2m.gene_reaction_rule='HGNC:2698 and HGNC:987 and HGNC:986 and HGNC:2898 or HGNC:2698 and HGNC:2898 and HGNC:987 and HGNC:986'cobra/io/sbml.py:235 �[1;31mUserWarning�[0m: M_h_x appears as a reactant and product FAOXC220200x
for rxex in Recon2.exchanges:
rxex.bounds=(0.0,10)
Recon2.reactions.get_by_id("DM_4hrpo").lower_bound=-0.012
Recon2.reactions.get_by_id("DM_datp_n_").lower_bound=-0.012
Recon2.reactions.get_by_id("DM_dctp_n_").lower_bound=-0.012
Recon2.reactions.get_by_id("DM_dgtp_n_").lower_bound=-0.012
Recon2.reactions.get_by_id("DM_dttp_n_").lower_bound=-0.012
Recon2.reactions.get_by_id("DM_Lcystin").lower_bound=-0.024
Recon2.reactions.get_by_id("DM_pe_hs_LPAREN_r_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_2hb_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_34hpp_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_3hpvs_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_3mob_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_4mop_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_ac_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_acac_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_acald_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_acetone_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_acgam_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_acmana_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_ade_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_adn_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_adpcbl_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_akg_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_ala_B_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_ala_D_LPAREN_e_RPAREN_").lower_bound=-0.04
Recon2.reactions.get_by_id("EX_ala_L_LPAREN_e_RPAREN_").lower_bound=-0.04
Recon2.reactions.get_by_id("EX_am9csa_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_amp_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_arab_L_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_arachd_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_arg_L_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_asn_L_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_asp_L_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_atp_LPAREN_e_RPAREN_").lower_bound=-0.8
Recon2.reactions.get_by_id("EX_bhb_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_btn_LPAREN_e_RPAREN_").lower_bound=-0.2
Recon2.reactions.get_by_id("EX_ca2_LPAREN_e_RPAREN_").lower_bound=-0.2
Recon2.reactions.get_by_id("EX_carn_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_caro_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_cgly_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_chol_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_chsterol_LPAREN_e_RPAREN_").lower_bound=-2
Recon2.reactions.get_by_id("EX_cit_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_cl_LPAREN_e_RPAREN_").lower_bound=-1
Recon2.reactions.get_by_id("EX_CLPND_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_co2_LPAREN_e_RPAREN_").lower_bound=0
Recon2.reactions.get_by_id("EX_creat_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_crn_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_crvnc_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_csa_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_csn_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_cys_L_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_cytd_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_dad_2_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_dag_hs_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_dcmp_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_dcyt_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_ddca_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_dgsn_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_dhdascb_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_din_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_dopa_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_drib_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_etoh_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_fald_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_fe2_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_fe2_LPAREN_e_RPAREN_").lower_bound=-0.545
Recon2.reactions.get_by_id("EX_fe3_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_fmn_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_fol_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_for_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_fru_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_fuc_L_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_fum_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_gal_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_gam_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_gchola_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_glc_LPAREN_e_RPAREN_").lower_bound=-1
Recon2.reactions.get_by_id("EX_glcur_LPAREN_e_RPAREN_").lower_bound=-0.032
Recon2.reactions.get_by_id("EX_gln_L_LPAREN_e_RPAREN_").lower_bound=-0.09
Recon2.reactions.get_by_id("EX_glu_L_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_gluala_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_gly_LPAREN_e_RPAREN_").lower_bound=-0.03
Recon2.reactions.get_by_id("EX_glyb_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_glyc_LPAREN_e_RPAREN_").lower_bound=-0.21
Recon2.reactions.get_by_id("EX_glyc3p_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_glygn2_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_gsn_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_gthox_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_gthrd_LPAREN_e_RPAREN_").lower_bound=-0.09
Recon2.reactions.get_by_id("EX_gua_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_h_LPAREN_e_RPAREN_").lower_bound=-1
Recon2.reactions.get_by_id("EX_h2o_LPAREN_e_RPAREN_").lower_bound=-10
Recon2.reactions.get_by_id("EX_ha_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_HC00250_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_HC01609_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_HC01610_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_hdca_LPAREN_e_RPAREN_").lower_bound=-0.3
Recon2.reactions.get_by_id("EX_hdcea_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_his_L_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_hxan_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_ile_L_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_inost_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_k_LPAREN_e_RPAREN_").lower_bound=-0.2
Recon2.reactions.get_by_id("EX_lac_L_LPAREN_e_RPAREN_").lower_bound=-0.09
Recon2.reactions.get_by_id("EX_lcts_LPAREN_e_RPAREN_").lower_bound=-0.5
Recon2.reactions.get_by_id("EX_leu_L_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_leuktrA4_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_leuktrD4_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_leuktrE4_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_lnlc_LPAREN_e_RPAREN_").lower_bound=-0.06
Recon2.reactions.get_by_id("EX_lnlnca_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_lnlncg_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_lpchol_hs_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_lys_L_LPAREN_e_RPAREN_").lower_bound=-0.03
Recon2.reactions.get_by_id("EX_mag_hs_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_mal_L_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_malt_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_man_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_meoh_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_met_L_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_n2m2nmasn_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_na1_LPAREN_e_RPAREN_").lower_bound=-1
Recon2.reactions.get_by_id("EX_nac_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_ncam_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_nh4_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_no2_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_o2_LPAREN_e_RPAREN_").lower_bound=-1
Recon2.reactions.get_by_id("EX_o2s_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_ocdca_LPAREN_e_RPAREN_").lower_bound=-0.07
Recon2.reactions.get_by_id("EX_ocdcea_LPAREN_e_RPAREN_").lower_bound=-0.012 ### ??
Recon2.reactions.get_by_id("EX_octa_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_orn_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_oxa_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_pe_hs_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_pglyc_hs_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_phe_L_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_pheme_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_pi_LPAREN_e_RPAREN_").lower_bound=-0.04
Recon2.reactions.get_by_id("EX_pnto_R_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_ppa_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_pro_L_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_prostgh2_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_ps_hs_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_ptrc_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_ptvstlac_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_pydam_LPAREN_e_RPAREN_").lower_bound=-1
Recon2.reactions.get_by_id("EX_pydx_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_pydx5p_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_pydxn_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_pyr_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_q10h2_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_retfa_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_retinol_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_retn_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_rib_D_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_ribflv_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_sbt_DASH_d_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_sel_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_ser_L_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_so4_LPAREN_e_RPAREN_").lower_bound=-0.05
Recon2.reactions.get_by_id("EX_sph1p_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_spmd_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_strch1_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_strch2_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_sucr_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_tag_hs_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_thm_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_thr_L_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_thymd_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_tre_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_trp_L_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_ttdca_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_tyr_L_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_ura_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_urea_LPAREN_e_RPAREN_").lower_bound=-0.4
Recon2.reactions.get_by_id("EX_uri_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_utp_LPAREN_e_RPAREN_").lower_bound=-0.02
Recon2.reactions.get_by_id("EX_val_L_LPAREN_e_RPAREN_").lower_bound=-0.03
Recon2.reactions.get_by_id("EX_xmp_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.get_by_id("EX_xyl_D_LPAREN_e_RPAREN_").lower_bound=-0.3
Recon2.reactions.get_by_id("EX_xylt_LPAREN_e_RPAREN_").lower_bound=-0.012
Recon2.reactions.biomass_reaction.bounds=(0.008, 0.05)
Recon2.reactions.EX_lac_D_LPAREN_e_RPAREN_.bounds=(-0.001,0.001)Recon2.reactions.get_by_id("biomass_DNA").reaction'0.941642857142857 datp_n + 0.674428571428572 dctp_n + 0.707 dgtp_n + 0.935071428571429 dttp_n --> biomass_DNA_c'
import pandas as pd
ub_scores_matrix =pd.read_csv("Binary_Byposys_RECON2_2.tsv",sep=",",index_col=0,header=0)
confidence_scores_matrix=ub_scores_matrix.copy()for model in ub_scores_matrix.columns:
#High Confidence rate
HC=ub_scores_matrix[model][ub_scores_matrix[model] >= 0.75].index.tolist()
confidence_scores_matrix[model][HC]=3
#Medium Confidence Rate
MC=ub_scores_matrix[model][(ub_scores_matrix[model] < 0.75) & (ub_scores_matrix[model] >=0.5) ].index.tolist()
confidence_scores_matrix[model][MC]=2
#Low
LC=ub_scores_matrix[model][(ub_scores_matrix[model] < 0.5) & (ub_scores_matrix[model] >=0.25) ].index.tolist()
confidence_scores_matrix[model][LC]=1
#unknown
ZC=ub_scores_matrix[model][(ub_scores_matrix[model] <.25) & (ub_scores_matrix[model] > 0) ].index.tolist()
confidence_scores_matrix[model][ZC]=0
#Negative
NC=ub_scores_matrix[model][(ub_scores_matrix[model] == 0)].index.tolist()
confidence_scores_matrix[model][NC]=-1
from corda import reaction_confidence
conf_CancerBiopsy = {}
conf_NormalBiopsy = {}
for r in Recon2.reactions:
if(r.gene_reaction_rule!=''):
conf_CancerBiopsy[r.id]=reaction_confidence(r.gene_reaction_rule,confidence_scores_matrix["MaxCancerBiopsy"])
conf_NormalBiopsy[r.id]=reaction_confidence(r.gene_reaction_rule,confidence_scores_matrix["MaxNormalBiopsy"])
else:
conf_CancerBiopsy[r.id]=1
conf_NormalBiopsy[r.id]=1%matplotlib inline
import pandas as pd
df=pd.DataFrame({'Cancer': conf_CancerBiopsy})
df.Cancer.value_counts() 1.0 3450
3.0 1441
0.0 1381
-1.0 1275
2.0 238
Name: Cancer, dtype: int64
conf_CancerBiopsy["DM_4hrpo"]=3
conf_CancerBiopsy["DM_datp_n_"]=3
conf_CancerBiopsy["DM_dctp_n_"]=3
conf_CancerBiopsy["DM_dgtp_n_"]=3
conf_CancerBiopsy["DM_dttp_n_"]=3
conf_CancerBiopsy["DM_Lcystin"]=3
conf_CancerBiopsy["DM_pe_hs_LPAREN_r_RPAREN_"]=3
conf_CancerBiopsy["EX_2hb_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_34hpp_"]=3
conf_CancerBiopsy["EX_3hpvs_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_3mob_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_4mop_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_ac_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_acac_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_acald_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_acetone_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_acgam_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_acmana_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_ade_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_adn_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_adpcbl_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_akg_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_ala_B_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_ala_D_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_ala_L_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_am9csa_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_amp_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_arab_L_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_arachd_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_arg_L_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_asn_L_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_asp_L_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_atp_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_bhb_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_btn_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_ca2_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_carn_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_caro_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_cgly_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_chol_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_chsterol_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_cit_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_cl_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_CLPND_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_co2_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_creat_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_crn_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_crvnc_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_csa_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_csn_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_cys_L_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_cytd_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_dad_2_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_dag_hs_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_dcmp_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_dcyt_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_ddca_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_dgsn_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_dhdascb_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_din_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_dopa_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_drib_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_etoh_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_fald_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_fe2_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_fe2_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_fe3_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_fmn_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_fol_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_for_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_fru_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_fuc_L_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_fum_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_gal_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_gam_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_gchola_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_glc_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_glcur_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_gln_L_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_glu_L_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_gluala_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_gly_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_glyb_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_glyc_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_glyc3p_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_glygn2_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_gsn_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_gthox_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_gthrd_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_gua_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_h_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_h2o_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_ha_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_HC00250_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_HC01609_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_HC01610_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_hdca_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_hdcea_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_his_L_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_hxan_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_ile_L_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_inost_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_k_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_lac_L_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_lac_D_LPAREN_e_RPAREN_"]=-1
conf_CancerBiopsy["EX_lcts_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_leu_L_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_leuktrA4_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_leuktrD4_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_leuktrE4_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_lnlc_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_lnlnca_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_lnlncg_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_lpchol_hs_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_lys_L_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_mag_hs_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_mal_L_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_malt_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_man_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_meoh_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_met_L_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_n2m2nmasn_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_na1_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_nac_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_ncam_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_nh4_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_no2_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_o2_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_o2s_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_ocdca_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_ocdcea_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_octa_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_orn_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_oxa_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_pe_hs_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_pglyc_hs_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_phe_L_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_pheme_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_pi_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_pnto_R_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_ppa_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_pro_L_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_prostgh2_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_ps_hs_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_ptrc_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_ptvstlac_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_pydam_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_pydx_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_pydx5p_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_pydxn_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_pyr_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_q10h2_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_retfa_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_retinol_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_retn_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_rib_D_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_ribflv_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_sbt_DASH_d_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_sel_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_ser_L_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_so4_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_sph1p_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_spmd_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_strch1_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_strch2_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_sucr_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_tag_hs_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_thm_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_thr_L_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_thymd_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_tre_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_trp_L_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_ttdca_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_tyr_L_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_ura_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_urea_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_uri_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_utp_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_val_L_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_xmp_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_xyl_D_LPAREN_e_RPAREN_"]=3
conf_CancerBiopsy["EX_xylt_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["DM_4hrpo"]=3
conf_NormalBiopsy["DM_datp_n_"]=3
conf_NormalBiopsy["DM_dctp_n_"]=3
conf_NormalBiopsy["DM_dgtp_n_"]=3
conf_NormalBiopsy["DM_dttp_n_"]=3
conf_NormalBiopsy["DM_Lcystin"]=3
conf_NormalBiopsy["DM_pe_hs_LPAREN_r_RPAREN_"]=3
conf_NormalBiopsy["EX_2hb_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_34hpp_"]=3
conf_NormalBiopsy["EX_3hpvs_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_3mob_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_4mop_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_ac_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_acac_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_acald_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_acetone_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_acgam_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_acmana_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_ade_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_adn_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_adpcbl_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_akg_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_ala_B_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_ala_D_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_ala_L_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_am9csa_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_amp_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_arab_L_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_arachd_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_arg_L_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_asn_L_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_asp_L_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_atp_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_bhb_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_btn_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_ca2_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_carn_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_caro_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_cgly_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_chol_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_chsterol_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_cit_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_cl_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_CLPND_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_co2_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_creat_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_crn_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_crvnc_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_csa_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_csn_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_cys_L_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_cytd_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_dad_2_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_dag_hs_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_dcmp_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_dcyt_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_ddca_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_dgsn_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_dhdascb_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_din_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_dopa_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_drib_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_etoh_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_fald_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_fe2_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_fe2_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_fe3_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_fmn_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_fol_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_for_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_fru_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_fuc_L_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_fum_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_gal_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_gam_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_gchola_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_glc_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_glcur_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_gln_L_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_glu_L_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_gluala_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_gly_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_glyb_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_glyc_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_glyc3p_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_glygn2_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_gsn_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_gthox_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_gthrd_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_gua_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_h_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_h2o_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_ha_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_HC00250_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_HC01609_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_HC01610_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_hdca_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_hdcea_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_his_L_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_hxan_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_ile_L_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_inost_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_k_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_lac_L_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_lac_D_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_lcts_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_leu_L_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_leuktrA4_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_leuktrD4_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_leuktrE4_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_lnlc_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_lnlnca_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_lnlncg_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_lpchol_hs_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_lys_L_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_mag_hs_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_mal_L_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_malt_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_man_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_meoh_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_met_L_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_n2m2nmasn_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_na1_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_nac_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_ncam_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_nh4_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_no2_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_o2_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_o2s_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_ocdca_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_ocdcea_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_octa_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_orn_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_oxa_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_pe_hs_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_pglyc_hs_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_phe_L_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_pheme_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_pi_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_pnto_R_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_ppa_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_pro_L_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_prostgh2_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_ps_hs_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_ptrc_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_ptvstlac_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_pydam_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_pydx_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_pydx5p_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_pydxn_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_pyr_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_q10h2_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_retfa_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_retinol_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_retn_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_rib_D_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_ribflv_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_sbt_DASH_d_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_sel_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_ser_L_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_so4_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_sph1p_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_spmd_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_strch1_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_strch2_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_sucr_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_tag_hs_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_thm_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_thr_L_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_thymd_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_tre_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_trp_L_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_ttdca_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_tyr_L_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_ura_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_urea_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_uri_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_utp_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_val_L_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_xmp_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_xyl_D_LPAREN_e_RPAREN_"]=3
conf_NormalBiopsy["EX_xylt_LPAREN_e_RPAREN_"]=3conf_CancerBiopsy["biomass_reaction"]=3
conf_CancerBiopsy["biomass_DNA"]=3
conf_CancerBiopsy["biomass_RNA"]=3
conf_CancerBiopsy["biomass_carbohydrate"]=3
conf_CancerBiopsy["biomass_lipid"]=3
conf_CancerBiopsy["biomass_other"]=3
conf_CancerBiopsy["biomass_protein"]=3
conf_CancerBiopsy["DM_atp_c_"]=3
conf_NormalBiopsy["biomass_reaction"]=3
conf_NormalBiopsy["biomass_DNA"]=3
conf_NormalBiopsy["biomass_RNA"]=3
conf_NormalBiopsy["biomass_carbohydrate"]=3
conf_NormalBiopsy["biomass_lipid"]=3
conf_NormalBiopsy["biomass_other"]=3
conf_NormalBiopsy["biomass_protein"]=3
conf_NormalBiopsy["DM_atp_c_"]=3metas = ['0.014 biomass_DNA_c + 0.058 biomass_RNA_c + 0.071 biomass_carbohydrate_c + 0.097 biomass_lipid_c + 0.054 biomass_other_c + 0.706 biomass_protein_c --> ', '3pg_c', '4abut_c', '4hpro_LT_c', 'accoa_m', 'accoa_m --> coa_m', 'ade_c', 'adn_c', 'adp_c', 'akg_m', 'ala_B_c', 'ala_L_c', 'amet_c', 'amp_c', 'arg_L_c', 'asn_L_c', 'asp_D_c', 'asp_L_c', 'atp_c', 'bhb_c', 'cdp_c', 'CE1936_c', 'chol_c', 'chsterol_c', 'cit_c', 'citr_L_c', 'cmp_c', 'creat_c', 'crm_hs_c', 'crtn_c', 'ctp_c', 'cys_L_c', 'dag_hs_c', 'dhap_c', 'e4p_c', 'f6p_c', 'fdp_c', 'fru_c', 'fum_c', 'g1p_c', 'g3p_c', 'g6p_c', 'gdp_c', 'glc_D_c', 'glc_D_e', 'glc_D_e --> glc_D_c', 'gln_L_m', 'gln_L_c', 'gln_L_e --> gln_L_c', 'glu_L_c', 'glyb_c', 'gly_c', 'gmp_c', 'gthox_c', 'gthrd_c', 'gua_c', 'HC00342_c', 'his_L_c', 'hxan_c', 'icit_c', 'ile_L_c', 'lac_L_c', 'leu_L_c', 'leu_L_c', 'lys_L_c', 'mag_hs_c', 'mal_L_c', 'met_L_c', 'nad_c', 'nadh_c', 'nadh_m', 'nad_m', 'nadp_c', 'nadph_c', 'nadph_m', 'nadph_m', 'nadp_m', 'oaa_m', 'orn_c', 'pa_hs_c', 'pe_hs_c', 'pep_c', 'phe_L_c', 'pmtcoa_c --> coa_c', 'pro_D_c', 'pro_L_c', 'ps_hs_c', 'ptrc_c', 'pyr_c', 'pyr_m', 'r5p_c', 'ru5p_D_c', 's7p_c', 'ser_L_c', 'spmd_c', 'succ_c', 'succoa_m --> coa_m', 'tag_hs_c', 'thr_L_c', 'trp_L_c', 'tym_c', 'tyr_L_c', 'udp_c', 'ump_c', 'utp_c', 'val_L_c']%%time
from corda import CORDA
opt_NormalBiopsy = CORDA(model=Recon2, confidence=conf_NormalBiopsy, n=5, met_prod=metas, penalty_factor=1000)
opt_NormalBiopsy.build()
print(opt_NormalBiopsy)
model_NormalBiopsy=opt_NormalBiopsy.cobra_model(name="NormalBiopsy")
print(model_NormalBiopsy.optimize())build status: reconstruction complete
Inc. reactions: 2351/7891
- unclear: 182/640
- exclude: 250/2368
- low and medium: 721/3507
- high: 1198/1376
<Solution 0.022 at 0x7f80e0007438>
CPU times: user 22min 4s, sys: 644 ms, total: 22min 4s
Wall time: 22min 4s
%%time
from corda import CORDA
opt_CancerBiopsy = CORDA(model=Recon2, confidence=conf_CancerBiopsy, n=5, met_prod=metas, penalty_factor=1000)
opt_CancerBiopsy.build()
print(opt_CancerBiopsy)
model_CancerBiopsy=opt_CancerBiopsy.cobra_model(name="CancerBiopsy")
print(model_CancerBiopsy.optimize())build status: reconstruction complete
Inc. reactions: 2720/7891
- unclear: 283/1381
- exclude: 155/1276
- low and medium: 734/3499
- high: 1548/1735
<Solution 0.033 at 0x7f80dfe476d8>
CPU times: user 23min 32s, sys: 644 ms, total: 23min 32s
Wall time: 23min 32s
cp=model_NormalBiopsy.copy()
cp.optimize()
cp.summary(fva=True)IN FLUXES OUT FLUXES OBJECTIVES
----------------------------------------------- ---------------------------------------------- ----------------------
id Flux Range id Flux Range biomass_reac... 0.022
--------------- -------- -------------------- --------------- -------- -------------------
glc_D_e 0.205 [0.00605, 1] h_e 0.431 [-0.977, 5.4]
o2_e 0.0294 [-0.0149, 1] lac_L_e 0.359 [-0.09, 2.81]
lys_L_e 0.013 [0.013, 0.013] pyr_e 0.0503 [-0.012, 2.75]
atp_e 0.0124 [-0.0325, 0.8] pi_e 0.0202 [0, 1.76]
gthrd_e 0.012 [-0.023, 0.09] glyc_S_e 0.0152 [0, 1.33]
leu_L_e 0.012 [0.012, 0.012] nh4_e 0.0147 [-0.012, 1.3]
ps_hs_e 0.012 [0.00391, 0.012] leuktrD4_e 0.012 [0, 0.012]
leuktrA4_e 0.012 [0, 0.012] xmp_e 0.0104 [-0.012, 0.832]
o2s_e 0.012 [0, 0.012] dag_hs_e 0.00785 [-0.000385, 0.0235]
ser_L_e 0.012 [0.012, -0.387] akg_e 0.00776 [-0.012, 0.371]
man_e 0.012 [0.012, -0.691] ala_L_e 0.00411 [-0.04, 0.359]
gly_e 0.0119 [0.03, -0.369] Rtotal_e 0.00325 [0, 0.395]
gln_L_e 0.0114 [0.09, -0.288] dgtp_m 0.00323 [0, 0.856]
pro_L_e 0.00907 [0.00907, 0.00907] co2_e 0.00314 [0, 1.79]
arg_L_e 0.0079 [0.0079, 0.0079] lac_D_e 0.001 [0, 0.001]
val_L_e 0.00776 [0.00776, 0.00776] for_e 0.000449 [-0.012, 0.04]
fum_e 0.00776 [0.012, -0.407] c8crn_e 0.000449 [0, 0.012]
thr_L_e 0.00688 [0.00688, 0.00688] ac_e 0 [-0.012, 2.03]
ile_L_e 0.00629 [0.00629, 0.012] dgtp_n 0 [-0.012, 0.844]
asn_L_e 0.00615 [0.00615, 0.00615] datp_m 0 [0, 0.833]
phe_L_e 0.00571 [0.00571, 0.012] amp_e 0 [-0.012, 0.833]
datp_n 0.00374 [0.012, -0.821] abt_e 0 [0, 0.774]
lpchol_hs_e 0.00363 [0, 0.0119] xylt_e 0 [-0.012, 0.762]
tyr_L_e 0.00351 [0.00351, 0.012] oxa_e 0 [0, 0.623]
met_L_e 0.00337 [0.00337, 0.012] aicar_e 0 [0, 0.614]
his_L_e 0.00278 [0, 0.012] ppi_e 0 [0, 0.586]
acac_e 0.00269 [-0.00931, 0.012] fe3_e 0 [-0.012, 0.545]
pe_hs_e 0.00137 [0.012, -0.0189] elaid_e 0 [0, 0.428]
biomass_other_c 0.00119 [0.00119, 0.00119] hdcea_e 0 [0, 0.428]
uri_e 0.00118 [0.012, -0.0538] ocdcea_e 0 [0, 0.428]
cys_L_e 0.00102 [0.00102, 0.012] vacc_e 0 [0, 0.428]
cytd_e 0.000859 [0.012, -0.0538] mal_L_e 0 [-0.012, 0.407]
inost_e 0.000513 [0.000513, 0.000513] 5oxpro_e 0 [0, 0.398]
arachd_e 0.000449 [0, 0.012] cit_e 0 [-0.012, 0.393]
crn_e 0.000449 [0, 0.012] gal_e 0 [0, 0.363]
sph1p_e 0.000385 [0.000385, 0.012] ade_e 0 [0, 0.356]
pglyc_hs_e 0.000321 [0.000321, 0.012] prpp_e 0 [0, 0.356]
trp_L_e 0.000293 [0.000293, 0.000293] nrvnc_e 0 [0, 0.272]
dttp_n 0.000288 [0.000288, -0.0117] cgly_e 0 [-0.012, 0.101]
dctp_n 0.000208 [0.012, -0.0538] glu_L_e 0 [-0.012, 0.101]
h2o_e 0 [-3.27, 3.59] clpnd_e 0 [0, 0.096]
fe2_e 0 [-0.012, 0.545] tmndnc_e 0 [0, 0.096]
hdca_e 0 [-0.0116, 0.3] eicostet_e 0 [0, 0.084]
ocdca_e 0 [0, 0.07] dlnlcg_e 0 [0, 0.072]
lnlc_e 0 [-0.012, 0.06] lnlncg_e 0 [0, 0.072]
3hpvs_e 0 [0, 0.012] lnlnca_e 0 [-0.012, 0.072]
3mob_e 0 [0, 0.012] gthox_e 0 [0, 0.0565]
4hpro_LT_m 0 [0, 0.012] utp_e 0 [-0.02, 0.0458]
4mop_e 0 [0, 0.012] pheme_e 0 [0, 0.0429]
arab_L_e 0 [0, 0.012] bilglcur_e 0 [0, 0.041]
asp_L_e 0 [0, 0.012] co_e 0 [0, 0.041]
carn_e 0 [0, 0.012] bildglcur_e 0 [0, 0.04]
crvnc_e 0 [0, 0.012] fald_e 0 [-0.012, 0.024]
csa_e 0 [0, 0.012] meoh_e 0 [-0.012, 0.024]
dopa_e 0 [0, 0.012] pe_hs_r 0 [-0.012, 0.0189]
etoh_e 0 [0, 0.012] cholate_e 0 [0, 0.0156]
fol_e 0 [0, 0.012] 3mlda_e 0 [0, 0.0126]
gam_e 0 [0, 0.012] 34dhoxpeg_e 0 [0, 0.012]
gluala_e 0 [0, 0.012] 3bcrn_e 0 [0, 0.012]
ha_e 0 [0, 0.012] 3ddcrn_e 0 [0, 0.012]
mag_hs_e 0 [0, 0.012] 3deccrn_e 0 [0, 0.012]
n2m2nmasn_e 0 [0, 0.012] 3hdececrn_e 0 [0, 0.012]
octa_e 0 [0, 0.012] 3hexdcrn_e 0 [0, 0.012]
ptvstlac_e 0 [0, 0.012] 3hpvstet_e 0 [0, 0.012]
retinol_e 0 [0, 0.012] 3ivcrn_e 0 [0, 0.012]
thymd_e 0 [0, 0.012] 3octdec2crn_e 0 [0, 0.012]
gchola_e 0 [-0.00355, 0.012] 3octdeccrn_e 0 [0, 0.012]
ppa_e 0 [-0.00926, 0.012] 3octdece1crn_e 0 [0, 0.012]
bhb_e 0 [-0.00931, 0.012] 3tdcrn_e 0 [0, 0.012]
glyc3p_e 0 [-0.0119, 0.012] 3tetd7ecoacrn_e 0 [0, 0.012]
HC01609_e 0 [-0.012, 0.012] 3thexddcoacrn_e 0 [0, 0.012]
HC01610_e 0 [-0.012, 0.012] 3ttetddcoacrn_e 0 [0, 0.012]
pnto_R_e 0 [0, 0.011] adrn_e 0 [0, 0.012]
dcmp_e 0 [0.012, -0.0538] am19cs_e 0 [0, 0.012]
am1csa_e 0 [0, 0.012]
am9csa_e 0 [0, 0.012]
c6crn_e 0 [0, 0.012]
fol_c 0 [0, 0.012]
ivcrn_e 0 [0, 0.012]
leuktrB4_e 0 [0, 0.012]
n5m2masn_g 0 [0, 0.012]
ptvstm3_e 0 [0, 0.012]
retn_e 0 [0, 0.012]
1glyc_hs_e 0 [0, 0.0117]
ethamp_r 0 [0, 0.0116]
fuc14galacgl... 0 [0, 0.0116]
octdececoa_c 0 [0, 0.011]
so4_e 0 [0, 0.011]
taur_c 0 [0, 0.011]
taur_e 0 [0, 0.011]
ahcys_e 0 [0, 0.00863]
4hphac_e 0 [0, 0.00849]
pchol_hs_e 0 [0, 0.00809]
pheacgln_e 0 [0, 0.00629]
HC00250_e 0 [0, 0.00549]
4mptnl_e 0 [0, 0.00355]
5adtststerone_e 0 [0, 0.00355]
andrstrn_e 0 [0, 0.00355]
andrstrnglc_e 0 [0, 0.00355]
aprgstrn_e 0 [0, 0.00355]
chsterol_e 0 [0, 0.00355]
glyc_e 0 [0.012, -0.21]
cp=model_CancerBiopsy.copy()
cp.optimize()
cp.summary(fva=True)IN FLUXES OUT FLUXES OBJECTIVES
----------------------------------------------- ------------------------------------------- -----------------------
id Flux Range id Flux Range biomass_reac... 0.0334
--------------- -------- -------------------- --------------- ------- -----------------
glc_D_e 0.357 [0.197, 1] h_e 0.793 [-0.411, 3.29]
o2_e 0.2 [-0.0058, 1] lac_L_e 0.456 [-0.09, 2.7]
gln_L_e 0.0886 [0.09, -0.153] pyr_e 0.174 [-0.012, 1.44]
lys_L_e 0.0198 [0.0198, 0.03] nh4_e 0.102 [-0.012, 0.475]
Lcystin_c 0.0175 [-0.00522, 0.024] cit_e 0.0771 [-0.012, 0.348]
arg_L_e 0.012 [0.012, 0.012] ala_L_e 0.0716 [-0.0169, 0.294]
asn_L_e 0.012 [0.00933, 0.012] h2o_e 0.0349 [-0.371, 1.69]
4mop_e 0.012 [0.00622, 0.012] co2_e 0.0242 [0, 1.73]
4hpro_LT_m 0.012 [0, 0.012] ac_e 0.0237 [-0.012, 0.504]
asp_L_e 0.012 [0, 0.012] urate_e 0.0228 [0, 0.0847]
dgsn_e 0.012 [0, 0.012] so4_e 0.0221 [0, 0.0584]
o2s_e 0.012 [0, 0.012] pi_e 0.0142 [-0.04, 0.119]
acac_e 0.012 [-0.012, 0.012] bhb_e 0.012 [-0.012, 0.012]
gsn_e 0.012 [0.012, -0.0228] glyc_e 0.0107 [-0.21, 0.299]
dctp_n 0.012 [0.012, -0.0409] uri_e 0.00708 [-0.012, 0.0634]
ps_hs_e 0.012 [0.012, -0.147] dag_hs_e 0.00665 [-0.012, 0.183]
ser_L_e 0.012 [0.012, -0.287] cys_L_e 0.00622 [-0.012, 0.0464]
akg_e 0.012 [0.012, -0.331] tchola_e 0.00511 [0, 0.0546]
val_L_e 0.0118 [-0.000222, 0.03] thymd_e 0.00268 [-0.012, 0.0994]
thr_L_e 0.0104 [0.0104, 0.012] 3deccrn_e 0.00204 [0, 0.012]
ile_L_e 0.00956 [0.00956, 0.012] lac_D_e 0.001 [-0.001, 0.001]
phe_L_e 0.00867 [0.00867, 0.012] fe3_e 0 [-0.012, 0.545]
3mob_e 0.0074 [0.012, -0.0182] oxa_e 0 [0, 0.452]
leu_L_e 0.00622 [0.00622, 0.012] vacc_e 0 [0, 0.452]
chol_e 0.00552 [-0.0119, 0.012] elaid_e 0 [0, 0.449]
tyr_L_e 0.00533 [0.00533, 0.012] no_e 0 [0, 0.429]
met_L_e 0.00511 [0.00511, 0.012] gal_e 0 [0, 0.401]
gchola_e 0.00511 [0.012, -0.0465] ocdcea_e 0 [0, 0.349]
ppa_e 0.00489 [0.012, -0.0625] xylt_e 0 [-0.012, 0.328]
his_L_e 0.00422 [0.00422, 0.012] hdcea_e 0 [0, 0.328]
pe_hs_e 0.00302 [0.012, -0.147] glyc_S_e 0 [0, 0.299]
arachd_e 0.00204 [0, 0.012] acmana_e 0 [0, 0.294]
crn_e 0.00204 [0, 0.012] pro_L_e 0 [-0.012, 0.287]
for_e 0.002 [0.012, -0.0999] ha_pre1_e 0 [0, 0.193]
biomass_other_c 0.0018 [0.0018, 0.0018] nrvnc_e 0 [0, 0.175]
dad_2_e 0.00179 [0, 0.012] ethamp_r 0 [0, 0.159]
cytd_e 0.00117 [0.012, -0.0634] pe_hs_r 0 [-0.012, 0.147]
gly_e 0.000893 [0.03, -0.269] ha_e 0 [-0.012, 0.0898]
inost_e 0.000779 [0.000779, 0.000779] clpnd_e 0 [0, 0.06]
hdca_e 0.000584 [-0.0294, 0.3] dlnlcg_e 0 [0, 0.06]
sph1p_e 0.000584 [0.012, -0.147] eicostet_e 0 [0, 0.06]
pglyc_hs_e 0.000487 [0.000487, 0.000487] lnlnca_e 0 [0, 0.06]
trp_L_e 0.000444 [0.000444, 0.012] lnlncg_e 0 [0, 0.06]
datp_n 0.00044 [0.00044, 0.00044] taur_c 0 [0, 0.0584]
dttp_n 0.000437 [0.000437, -0.0524] taur_e 0 [0, 0.0584]
dgtp_n 0.000331 [0.000331, 0.000331] chsterol_e 0 [0, 0.0524]
fe2_e 0 [-0.012, 0.545] 4mptnl_e 0 [0, 0.0511]
ocdca_e 0 [0, 0.07] aprgstrn_e 0 [0, 0.0511]
lnlc_e 0 [0, 0.06] 5adtststerone_e 0 [0, 0.0495]
utp_e 0 [0, 0.02] andrstrn_e 0 [0, 0.0495]
3hpvs_e 0 [0, 0.012] fuc13galacgl... 0 [0, 0.048]
amp_e 0 [0, 0.012] fuc14galacgl... 0 [0, 0.048]
arab_L_e 0 [0, 0.012] galfucgalacg... 0 [0, 0.0456]
crvnc_e 0 [0, 0.012] adn_e 0 [-0.00868, 0.045]
dcyt_e 0 [0, 0.012] 5adtststeron... 0 [0, 0.0441]
din_e 0 [0, 0.012] andrstrnglc_e 0 [0, 0.0441]
dopa_e 0 [0, 0.012] tststeroneglc_e 0 [0, 0.044]
etoh_e 0 [0, 0.012] man_e 0 [-0.012, 0.036]
fmn_e 0 [0, 0.012] fuc_L_e 0 [0, 0.0347]
gam_e 0 [0, 0.012] 13_cis_retng... 0 [0, 0.024]
gluala_e 0 [0, 0.012] gthox_e 0 [0, 0.024]
leuktrA4_e 0 [0, 0.012] retnglc_e 0 [0, 0.024]
n2m2nmasn_e 0 [0, 0.012] fald_e 0 [-0.012, 0.024]
orn_e 0 [0, 0.012] meoh_e 0 [-0.012, 0.024]
ptrc_e 0 [0, 0.012] glyb_e 0 [0, 0.0238]
ptvstlac_e 0 [0, 0.012] 1mncam_e 0 [0, 0.0236]
retinol_e 0 [0, 0.012] Rtotal_e 0 [0, 0.0235]
spmd_e 0 [0, 0.012] lpchol_hs_e 0 [0, 0.0235]
2hb_e 0 [-0.00156, 0.012] pchol_hs_e 0 [0, 0.0235]
HC01609_e 0 [-0.012, 0.012] ppi_e 0 [0, 0.02]
HC01610_e 0 [-0.012, 0.012] ump_e 0 [0, 0.02]
fucfucfucgal... 0 [0, 0.016]
34dhoxpeg_e 0 [0, 0.012]
3bcrn_e 0 [0, 0.012]
3ddcrn_e 0 [0, 0.012]
3hdececrn_e 0 [0, 0.012]
3hexdcrn_e 0 [0, 0.012]
3hpvstet_e 0 [0, 0.012]
3ivcrn_e 0 [0, 0.012]
3octdec2crn_e 0 [0, 0.012]
3octdeccrn_e 0 [0, 0.012]
3octdece1crn_e 0 [0, 0.012]
3tdcrn_e 0 [0, 0.012]
3tetd7ecoacrn_e 0 [0, 0.012]
3thexddcoacrn_e 0 [0, 0.012]
3ttetddcoacrn_e 0 [0, 0.012]
4abutn_e 0 [0, 0.012]
Asn_X_Ser_Thr_l 0 [0, 0.012]
CE1940_e 0 [0, 0.012]
abt_e 0 [0, 0.012]
ade_e 0 [0, 0.012]
adrn_e 0 [0, 0.012]
c6crn_e 0 [0, 0.012]
leuktrB4_e 0 [0, 0.012]
leuktrD4_e 0 [0, 0.012]
n5m2masn_g 0 [0, 0.012]
prpp_e 0 [0, 0.012]
ptvst_e 0 [0, 0.012]
ribflv_e 0 [0, 0.012]
retn_e 0 [-0.012, 0.012]
anth_c 0 [0, 0.0116]
c5dc_e 0 [0, 0.0102]
3mlda_e 0 [0, 0.00778]
5mta_e 0 [0, 0.00689]
sprm_c 0 [0, 0.00689]
sprm_e 0 [0, 0.00689]
4hphac_e 0 [0, 0.00667]
q10h2_e 0 [0, 0.00667]
ivcrn_e 0 [0, 0.00578]
bilglcur_e 0 [0, 0.00528]
co_e 0 [0, 0.00528]
pheme_e 0 [0, 0.00528]
pheacgln_e 0 [0, 0.00333]
nac_e 0 [0.0116, -0.012]
gthrd_e 0 [0.0584, -0.06]
model_CancerBiopsy.optimize()
model_CancerBiopsy.metabolites.atp_c.summary()
print("ATP production")
print(0.681+0.681+0.0178+0.0117)
print("ATP consumption (not in biomass)")
print(0.324+0.321+0.012+0.012+0.0107)PRODUCING REACTIONS -- ATP(4-) (atp_c)
--------------------------------------
% FLUX RXN ID REACTION
--- ------ ---------- --------------------------------------------------
50% 0.686 PGK 3pg_c + atp_c <=> 13dpg_c + adp_c
50% 0.686 PYK adp_c + h_c + pep_c --> atp_c + pyr_c
1% 0.0115 CYTK2 atp_c + dcmp_c <=> adp_c + dcdp_c
CONSUMING REACTIONS -- ATP(4-) (atp_c)
--------------------------------------
% FLUX RXN ID REACTION
--- ------ ---------- --------------------------------------------------
50% 0.69 biomass... 0.716189801699717 ala_L_c + 0.508866855524079 a...
24% 0.325 PFK atp_c + f6p_c --> adp_c + fdp_c + h_c
23% 0.322 HEX1 atp_c + glc_D_c --> adp_c + g6p_c + h_c
1% 0.0142 NICRNS atp_c + nicrns_c --> adp_c + h_c + nicrnt_c
1% 0.012 HEX10 atp_c + gam_c --> adp_c + gam6p_c + h_c
1% 0.0107 GLYK atp_c + glyc_c --> adp_c + glyc3p_c + h_c
ATP production
1.3915000000000002
ATP consumption (not in biomass)
0.6797000000000001
model_NormalBiopsy.optimize()
model_NormalBiopsy.metabolites.atp_c.summary()
model_NormalBiopsy.metabolites.atp_m.summary()
print("ATP production")
print(0.387+0.385+0.0763+0.0858)
print("ATP consumption (not in biomass)")
print(0.186+0.162+0.012+0.012+0.0763+0.0104)PRODUCING REACTIONS -- ATP(4-) (atp_c)
--------------------------------------
% FLUX RXN ID REACTION
--- ------ ---------- --------------------------------------------------
50% 0.416 PGK 3pg_c + atp_c <=> 13dpg_c + adp_c
50% 0.416 PYK adp_c + h_c + pep_c --> atp_c + pyr_c
CONSUMING REACTIONS -- ATP(4-) (atp_c)
--------------------------------------
% FLUX RXN ID REACTION
--- ------ ---------- --------------------------------------------------
55% 0.454 biomass... 0.716189801699717 ala_L_c + 0.508866855524079 a...
25% 0.206 PFK atp_c + f6p_c --> adp_c + fdp_c + h_c
17% 0.138 HEX7 atp_c + fru_c --> adp_c + f6p_c + h_c
1% 0.012 HEX4 atp_c + man_c --> adp_c + h_c + man6p_c
PRODUCING REACTIONS -- ATP(4-) (atp_m)
--------------------------------------
% FLUX RXN ID REACTION
---- ------ -------- --------------------------------------------------
100% 0.0579 ATPS4m adp_m + 4.0 h_i + pi_m --> atp_m + h2o_m + 3.0 h_m
CONSUMING REACTIONS -- ATP(4-) (atp_m)
--------------------------------------
% FLUX RXN ID REACTION
---- ------ -------- --------------------------------------------------
112% 0.0651 ADK1m amp_m + atp_m <=> 2.0 adp_m
ATP production
0.9341
ATP consumption (not in biomass)
0.45870000000000005
# Production of ATP from glucose in anaerobic conditions for Cancer Biopsies
# test for max ATP hydrolysis flux from only glucose
closedModel=model_CancerBiopsy.copy()
closedModel.objective="DM_atp_c_"
for rx in closedModel.exchanges:
rx.upper_bound= 10
rx.lower_bound= -0.01
######################################################################
## Glucose aerobic
######################################################################
closedModel.reactions.EX_h2o_LPAREN_e_RPAREN_.bounds=(-10,10)
closedModel.reactions.EX_h_LPAREN_e_RPAREN_.bounds=(-10,10)
closedModel.reactions.EX_glc_LPAREN_e_RPAREN_.bounds=(-1,-1)
closedModel.reactions.EX_gln_L_LPAREN_e_RPAREN_.bounds=(0,0)
closedModel.reactions.EX_o2_LPAREN_e_RPAREN_.bounds=(-1,-1)
closedModel.reactions.EX_co2_LPAREN_e_RPAREN_.bounds=(0,10)
closedModel.reactions.EX_pi_LPAREN_e_RPAREN_.bounds=(-10,10)
FBA = cobra.flux_analysis.pfba(closedModel)
print("===========================")
print("Glucose aerobic")
print("===========================")
print("Oxigen use",closedModel.reactions.EX_o2_LPAREN_e_RPAREN_.reaction,FBA["EX_o2_LPAREN_e_RPAREN_"])
print("H2O",closedModel.reactions.EX_h2o_LPAREN_e_RPAREN_.reaction,FBA["EX_h2o_LPAREN_e_RPAREN_"])
print("CO2 production",closedModel.reactions.EX_co2_LPAREN_e_RPAREN_.reaction,FBA["EX_co2_LPAREN_e_RPAREN_"])
print("Glucose consumption",closedModel.reactions.EX_glc_LPAREN_e_RPAREN_.reaction,FBA["EX_glc_LPAREN_e_RPAREN_"])
print("Glutamine consumption",closedModel.reactions.EX_gln_L_LPAREN_e_RPAREN_.reaction,FBA["EX_gln_L_LPAREN_e_RPAREN_"])
print("ATP production",FBA["DM_atp_c_"])
closedModel.summary(fva=True)
######################################################################
## Glucose anaerobic
######################################################################
closedModel.reactions.EX_h2o_LPAREN_e_RPAREN_.bounds=(-10,10)
closedModel.reactions.EX_h_LPAREN_e_RPAREN_.bounds=(-10,10)
closedModel.reactions.EX_glc_LPAREN_e_RPAREN_.bounds=(-1,-1)
closedModel.reactions.EX_gln_L_LPAREN_e_RPAREN_.bounds=(0,0)
closedModel.reactions.EX_o2_LPAREN_e_RPAREN_.bounds=(0,0)
closedModel.reactions.EX_co2_LPAREN_e_RPAREN_.bounds=(0,10)
closedModel.reactions.EX_pi_LPAREN_e_RPAREN_.bounds=(-10,10)
FBA = cobra.flux_analysis.pfba(closedModel)
print("===========================")
print("Glucose anaerobic")
print("===========================")
print("Oxigen use",closedModel.reactions.EX_o2_LPAREN_e_RPAREN_.reaction,FBA["EX_o2_LPAREN_e_RPAREN_"])
print("H2O",closedModel.reactions.EX_h2o_LPAREN_e_RPAREN_.reaction,FBA["EX_h2o_LPAREN_e_RPAREN_"])
print("CO2 production",closedModel.reactions.EX_co2_LPAREN_e_RPAREN_.reaction,FBA["EX_co2_LPAREN_e_RPAREN_"])
print("Glucose consumption",closedModel.reactions.EX_glc_LPAREN_e_RPAREN_.reaction,FBA["EX_glc_LPAREN_e_RPAREN_"])
print("Glutamine consumption",closedModel.reactions.EX_gln_L_LPAREN_e_RPAREN_.reaction,FBA["EX_gln_L_LPAREN_e_RPAREN_"])
print("ATP production",FBA["DM_atp_c_"])
closedModel.summary(fva=True)===========================
Glucose aerobic
===========================
Oxigen use o2_e <-- -1.0
H2O h2o_e <=> 0.624498876
CO2 production co2_e --> 0.629498876
Glucose consumption glc_D_e <-- -1.0
Glutamine consumption gln_L_e --> 0.0
ATP production 1.95814078667
IN FLUXES OUT FLUXES OBJECTIVES
----------------------------------------------- ------------------------------------------- ---------------
id Flux Range id Flux Range DM_atp_c_ 1.96
--------------- -------- -------------------- ----------- -------- --------------------
glc_D_e 1 [1, 1] h_e 2.11 [1.63, 2.36]
o2_e 1 [1, 1] lac_D_e 1.7 [-0.01, 1.9]
3mob_e 0.01 [0.01, 0.01] co2_e 0.629 [0.498, 1.05]
dctp_n 0.01 [0.01, 0.01] h2o_e 0.624 [0.468, 1]
dgsn_e 0.01 [0.01, 0.01] pyr_e 0.297 [-0.01, 0.461]
din_e 0.01 [0.01, 0.01] nh4_e 0.194 [-0.00548, 0.223]
gam_e 0.01 [0.01, 0.01] ac_e 0.0592 [0.0297, 0.0592]
glyc_e 0.01 [0.01, 0.01] pi_e 0.0512 [0.0317, 0.101]
gsn_e 0.01 [0.01, 0.01] urate_e 0.0297 [0.0297, 0.0297]
ps_hs_e 0.01 [0.01, 0.01] so4_e 0.0296 [0, 0.0296]
ser_L_e 0.01 [0.01, 0.01] dag_hs_e 0.028 [0.00849, 0.028]
val_L_e 0.01 [0.01, 0.01] oxa_e 0.0257 [0, 0.0257]
xylt_e 0.01 [0.01, 0.01] ala_L_e 0.0227 [0.0128, 0.123]
ile_L_e 0.01 [0.00229, 0.01] for_e 0.0198 [-5e-05, 0.0298]
asn_L_e 0.01 [0.00224, 0.01] uri_e 0.019 [0.00903, 0.039]
tyr_L_e 0.01 [0.00128, 0.01] ppa_e 0.01 [-0.01, 0.0252]
trp_L_e 0.01 [0.000106, 0.01] 34dhoxpeg_e 0.01 [0, 0.01]
cytd_e 0.01 [5.4e-05, 0.01] leuktrB4_e 0.01 [0, 0.01]
4hpro_LT_m 0.01 [0, 0.01] retn_e 0.01 [0, 0.01]
crn_e 0.01 [0, 0.01] nac_e 0.00989 [0, 0.00989]
dopa_e 0.01 [0, 0.01] 4hphac_e 0.00872 [0, 0.00872]
etoh_e 0.01 [0, 0.01] 3ivcrn_e 0.00634 [0, 0.01]
gthrd_e 0.01 [0, 0.01] CE1940_e 0.005 [0, 0.005]
leuktrA4_e 0.01 [0, 0.01] gthox_e 0.005 [0, 0.005]
orn_e 0.01 [0, 0.01] c5dc_e 0.00366 [0, 0.00526]
retinol_e 0.01 [0, 0.01] ptvst_e 0.000898 [0, 0.01]
Lcystin_c 0.01 [-0.00481, 0.01] thymd_e 0.000213 [0.000213, 0.000213]
2hb_e 0.01 [-0.0075, 0.01] lac_L_e 0 [-0.01, 1.9]
pe_hs_e 0.01 [-0.0095, 0.01] cit_e 0 [-0.01, 0.104]
pe_hs_r 0.01 [-0.0095, 0.01] ppi_e 0 [-0.01, 0.02]
meoh_e 0.01 [0.01, -0.01] 3bcrn_e 0 [0, 0.01]
gly_e 0.01 [0.01, -0.0157] abt_e 0 [0, 0.01]
cys_L_e 0.01 [0.01, -0.0196] ivcrn_e 0 [0, 0.01]
pro_L_e 0.01 [0.01, -0.0906] leuktrD4_e 0 [0, 0.01]
lys_L_e 0.0084 [0.00474, 0.01] lpchol_hs_e 0 [0, 0.01]
spmd_e 0.005 [0, 0.005] ribflv_e 0 [0, 0.01]
leu_L_e 0.00436 [-0.00564, 0.01] vacc_e 0 [0, 0.01]
arachd_e 0.00366 [0, 0.00549] HC01609_e 0 [-0.01, 0.01]
arg_L_e 0.00287 [0.00287, 0.00287] HC01610_e 0 [-0.01, 0.01]
asp_L_e 0.00282 [0, 0.01] acac_e 0 [-0.01, 0.01]
thr_L_e 0.0025 [0.0025, 0.01] ade_e 0 [-0.01, 0.01]
phe_L_e 0.00208 [0.00208, 0.00208] amp_e 0 [-0.01, 0.01]
akg_e 0.00203 [0.01, -0.104] bhb_e 0 [-0.01, 0.01]
chol_e 0.00132 [0.00132, 0.01] fald_e 0 [-0.01, 0.01]
met_L_e 0.00122 [0.00122, 0.00122] fe2_e 0 [-0.01, 0.01]
his_L_e 0.00101 [0.00101, 0.00101] fe3_e 0 [-0.01, 0.01]
ptvstlac_e 0.000898 [0, 0.01] prpp_e 0 [-0.01, 0.01]
biomass_other_c 0.000432 [0.000432, 0.000432] sprm_c 0 [-0.01, 0.01]
adn_e 0.00043 [0.00043, 0.00043] sprm_e 0 [-0.01, 0.01]
inost_e 0.000187 [0.000187, 0.000187] taur_e 0 [-0.01, 0.01]
sph1p_e 0.00014 [0.00014, 0.00014] ump_e 0 [-0.01, 0.01]
Rtotal_e 0.00014 [0.00014, -0.01] anth_c 0 [0, 0.00989]
pglyc_hs_e 0.000117 [0.000117, 0.000117] glyb_e 0 [0, 0.00868]
datp_n 0.000105 [0.000105, 0.000105] 4abutn_e 0 [0, 0.005]
dttp_n 0.000105 [0.000105, 0.000105] 3deccrn_e 0 [0, 0.00366]
dgtp_n 7.9e-05 [7.9e-05, 7.9e-05] c6crn_e 0 [0, 0.00366]
arab_L_e 0 [0, 0.01]
fmn_e 0 [0, 0.01]
o2s_e 0 [0, 0.01]
ocdca_e 0 [0, 0.01]
pchol_hs_e 0 [0, 0.01]
utp_e 0 [0, 0.01]
4mop_e 0 [-0.00564, 0.01]
hdca_e 0 [0, 0.00563]
ptrc_e 0 [0, 0.005]
taur_c 0 [0.01, -0.01]
===========================
Glucose anaerobic
===========================
Oxigen use o2_e --> 0.0
H2O h2o_e <=> -0.00965014711111
CO2 production co2_e --> 0.0
Glucose consumption glc_D_e <-- -1.0
Glutamine consumption gln_L_e --> 0.0
ATP production 1.86504778133
IN FLUXES OUT FLUXES OBJECTIVES
----------------------------------------------- ----------------------------------------- ---------------
id Flux Range id Flux Range DM_atp_c_ 1.87
--------------- -------- -------------------- ----------- ------- -------------------
glc_D_e 1 [1, 1] h_e 2.02 [1.92, 2.08]
dctp_n 0.01 [0.01, 0.01] lac_D_e 1.99 [-0.01, 2.07]
gam_e 0.01 [0.01, 0.01] pyr_e 0.0332 [-0.01, 0.129]
o2s_e 0.01 [0.01, 0.01] pi_e 0.0317 [0.0317, 0.0919]
ps_hs_e 0.01 [0.01, 0.01] nh4_e 0.0173 [0.00721, 0.049]
leu_L_e 0.01 [-0.00461, 0.01] thymd_e 0.00992 [0.00593, 0.00992]
for_e 0.00976 [0.00976, -0.0117] dag_hs_e 0.00849 [0.00849, 0.0187]
h2o_e 0.00965 [-0.0325, 0.0762] 4mop_e 0.00564 [0.00564, -0.01]
glyc_e 0.00965 [-0.00754, 0.01] ser_L_e 0.00277 [0.00681, -0.01]
akg_e 0.00757 [-0.00851, 0.01] 3mob_e 0.00194 [0.00718, -0.00743]
val_L_e 0.00476 [-0.00461, 0.01] lac_L_e 0 [-0.01, 2.07]
lys_L_e 0.00474 [0.00474, 0.00474] co2_e 0 [0, 0.0825]
gly_e 0.00431 [0.00431, -0.0157] ppi_e 0 [-0.01, 0.02]
arg_L_e 0.00287 [0.00287, 0.00287] cys_L_e 0 [-0.01, 0.0196]
pro_L_e 0.00257 [0.0033, -0.0289] glyc_S_e 0 [0, 0.0168]
thr_L_e 0.0025 [0.0025, 0.01] ppa_e 0 [0, 0.0153]
ile_L_e 0.00229 [0.00229, 0.00229] ala_L_e 0 [-0.00404, 0.0128]
asn_L_e 0.00224 [0.00224, 0.01] cit_e 0 [-0.01, 0.0118]
phe_L_e 0.00208 [0.00208, 0.00208] oxa_e 0 [0, 0.0105]
asp_L_e 0.00168 [0, 0.01] 3bcrn_e 0 [0, 0.01]
chol_e 0.00132 [0.00132, 0.00132] abt_e 0 [0, 0.01]
tyr_L_e 0.00128 [0.00128, 0.00128] fe2_e 0 [0, 0.01]
met_L_e 0.00122 [0.00122, 0.00122] ivcrn_e 0 [0, 0.01]
his_L_e 0.00101 [0.00101, 0.00101] leuktrB4_e 0 [0, 0.01]
acac_e 0.000898 [-0.01, 0.01] leuktrD4_e 0 [0, 0.01]
pe_hs_e 0.000497 [-0.0095, 0.01] lpchol_hs_e 0 [0, 0.01]
biomass_other_c 0.000432 [0.000432, 0.000432] ptvst_e 0 [0, 0.01]
adn_e 0.00043 [0.00043, 0.00043] retn_e 0 [0, 0.01]
uri_e 0.000428 [0.000428, -0.032] ribflv_e 0 [0, 0.01]
cytd_e 0.000312 [0, 0.01] HC01609_e 0 [-0.01, 0.01]
gsn_e 0.000289 [0.000289, 0.00428] ade_e 0 [-0.01, 0.01]
inost_e 0.000187 [0.000187, 0.000187] amp_e 0 [-0.01, 0.01]
Lcystin_c 0.000186 [-0.00481, 0.01] bhb_e 0 [-0.01, 0.01]
sph1p_e 0.00014 [0.00014, 0.00014] fald_e 0 [-0.01, 0.01]
Rtotal_e 0.00014 [0.00014, -0.01] sprm_e 0 [-0.01, 0.01]
pglyc_hs_e 0.000117 [0.000117, 0.000117] taur_c 0 [-0.01, 0.01]
trp_L_e 0.000106 [0.000106, 0.000106] taur_e 0 [-0.01, 0.01]
datp_n 0.000105 [0.000105, 0.000105] ump_e 0 [-0.01, 0.01]
dttp_n 0.000105 [0.000105, 0.000105] 3deccrn_e 0 [0, 0.00049]
dgtp_n 7.9e-05 [7.9e-05, 7.9e-05]
4hpro_LT_m 0 [0, 0.01]
arab_L_e 0 [0, 0.01]
crn_e 0 [0, 0.01]
etoh_e 0 [0, 0.01]
fe3_e 0 [0, 0.01]
fmn_e 0 [0, 0.01]
gthrd_e 0 [0, 0.01]
leuktrA4_e 0 [0, 0.01]
pchol_hs_e 0 [0, 0.01]
ptvstlac_e 0 [0, 0.01]
retinol_e 0 [0, 0.01]
utp_e 0 [0, 0.01]
xylt_e 0 [0, 0.01]
2hb_e 0 [-0.0075, 0.01]
pe_hs_r 0 [-0.0095, 0.01]
HC01610_e 0 [-0.01, 0.01]
meoh_e 0 [-0.01, 0.01]
prpp_e 0 [-0.01, 0.01]
din_e 0 [0, 0.00528]
arachd_e 0 [0, 0.00049]
hdca_e 0 [0, 0.00014]
urate_e 0 [0, -0.00528]
sprm_c 0 [0.01, -0.01]
ac_e 0 [0, -0.0168]
# Production of ATP from glucose in anaerobic conditions for Cancer Biopsies
# test for max ATP hydrolysis flux from only glucose
closedModel=model_NormalBiopsy.copy()
closedModel.objective="DM_atp_c_"
for rx in closedModel.exchanges:
rx.upper_bound= 10
rx.lower_bound= -0.01
######################################################################
## Glucose aerobic
######################################################################
closedModel.reactions.EX_h2o_LPAREN_e_RPAREN_.bounds=(-10,10)
closedModel.reactions.EX_h_LPAREN_e_RPAREN_.bounds=(-10,10)
closedModel.reactions.EX_glc_LPAREN_e_RPAREN_.bounds=(-1,-1)
closedModel.reactions.EX_gln_L_LPAREN_e_RPAREN_.bounds=(0,0)
closedModel.reactions.EX_o2_LPAREN_e_RPAREN_.bounds=(-1,-1)
closedModel.reactions.EX_co2_LPAREN_e_RPAREN_.bounds=(0,10)
closedModel.reactions.EX_pi_LPAREN_e_RPAREN_.bounds=(-10,10)
FBA = cobra.flux_analysis.pfba(closedModel)
print("===========================")
print("Glucose aerobic")
print("===========================")
print("Oxigen use",closedModel.reactions.EX_o2_LPAREN_e_RPAREN_.reaction,FBA["EX_o2_LPAREN_e_RPAREN_"])
print("H2O",closedModel.reactions.EX_h2o_LPAREN_e_RPAREN_.reaction,FBA["EX_h2o_LPAREN_e_RPAREN_"])
print("CO2 production",closedModel.reactions.EX_co2_LPAREN_e_RPAREN_.reaction,FBA["EX_co2_LPAREN_e_RPAREN_"])
print("Glucose consumption",closedModel.reactions.EX_glc_LPAREN_e_RPAREN_.reaction,FBA["EX_glc_LPAREN_e_RPAREN_"])
print("Glutamine consumption",closedModel.reactions.EX_gln_L_LPAREN_e_RPAREN_.reaction,FBA["EX_gln_L_LPAREN_e_RPAREN_"])
print("ATP production",FBA["DM_atp_c_"])
closedModel.summary(fva=True)
######################################################################
## Glucose anaerobic
######################################################################
closedModel.reactions.EX_h2o_LPAREN_e_RPAREN_.bounds=(-10,10)
closedModel.reactions.EX_h_LPAREN_e_RPAREN_.bounds=(-10,10)
closedModel.reactions.EX_glc_LPAREN_e_RPAREN_.bounds=(-1,-1)
closedModel.reactions.EX_gln_L_LPAREN_e_RPAREN_.bounds=(0,0)
closedModel.reactions.EX_o2_LPAREN_e_RPAREN_.bounds=(0,0)
closedModel.reactions.EX_co2_LPAREN_e_RPAREN_.bounds=(0,10)
closedModel.reactions.EX_pi_LPAREN_e_RPAREN_.bounds=(-10,10)
FBA = cobra.flux_analysis.pfba(closedModel)
print("===========================")
print("Glucose anaerobic")
print("===========================")
print("Oxigen use",closedModel.reactions.EX_o2_LPAREN_e_RPAREN_.reaction,FBA["EX_o2_LPAREN_e_RPAREN_"])
print("H2O",closedModel.reactions.EX_h2o_LPAREN_e_RPAREN_.reaction,FBA["EX_h2o_LPAREN_e_RPAREN_"])
print("CO2 production",closedModel.reactions.EX_co2_LPAREN_e_RPAREN_.reaction,FBA["EX_co2_LPAREN_e_RPAREN_"])
print("Glucose consumption",closedModel.reactions.EX_glc_LPAREN_e_RPAREN_.reaction,FBA["EX_glc_LPAREN_e_RPAREN_"])
print("Glutamine consumption",closedModel.reactions.EX_gln_L_LPAREN_e_RPAREN_.reaction,FBA["EX_gln_L_LPAREN_e_RPAREN_"])
print("ATP production",FBA["DM_atp_c_"])
closedModel.summary(fva=True)===========================
Glucose aerobic
===========================
Oxigen use o2_e <-- -1.0
H2O h2o_e <=> 1.90562345067
CO2 production co2_e --> 0.008321576
Glucose consumption glc_D_e <-- -1.0
Glutamine consumption gln_L_e --> 0.0
ATP production 3.91671747733
IN FLUXES OUT FLUXES OBJECTIVES
----------------------------------------------- ----------------------------------------- ---------------
id Flux Range id Flux Range DM_atp_c_ 3.92
--------------- -------- -------------------- ---------- -------- -------------------
glc_D_e 1 [1, 1] h_e 2.1 [2.04, 2.41]
o2_e 1 [1, 1] pyr_e 2.02 [1.77, 2.09]
akg_e 0.01 [0.01, 0.01] h2o_e 1.91 [1.58, 1.96]
gam_e 0.01 [0.01, 0.01] lac_L_e 0.0743 [-0.01, 0.375]
glyc3p_e 0.01 [0.01, 0.01] nh4_e 0.0318 [0.0287, 0.0531]
ha_e 0.01 [0.01, 0.01] ac_e 0.0241 [0.02, 0.0693]
man_e 0.01 [0.01, 0.01] abt_e 0.02 [0, 0.04]
o2s_e 0.01 [0.01, 0.01] cit_e 0.0124 [-0.01, 0.0163]
glu_L_e 0.00852 [-0.00148, 0.01] co2_e 0.00832 [0, 0.0483]
acac_e 0.0057 [0.00258, 0.01] oxa_e 0.00472 [0, 0.049]
lys_L_e 0.00474 [0.00474, 0.00474] bhb_e 0.00472 [0.0016, 0.00902]
4hpro_LT_m 0.00472 [0.0016, 0.00902] 5oxpro_e 0.00404 [0, 0.01]
leu_L_e 0.00436 [0.00436, 0.00436] dctp_n 0.00309 [-0.01, 0.015]
gly_e 0.00431 [0.00431, -0.0199] Rtotal_e 0.00118 [0.00118, 0.0397]
gluala_e 0.00404 [0, 0.01] tmndnc_e 0.000979 [0.000979, 0.01]
etoh_e 0.00376 [0, 0.01] for_e 0.000163 [0.000163, 0.0202]
pro_L_e 0.0033 [0.0033, 0.0033] lac_D_e 0 [0, 0.385]
dcmp_e 0.00316 [0.01, -0.0196] pi_e 0 [0, 0.0838]
arg_L_e 0.00287 [0.00287, 0.00287] ppi_e 0 [-0.01, 0.0379]
val_L_e 0.00282 [0.00282, 0.00282] mal_L_e 0 [-0.01, 0.0374]
thr_L_e 0.0025 [0.0025, 0.0025] ala_L_e 0 [-0.01, 0.0302]
fum_e 0.00245 [0.01, -0.0374] xylt_e 0 [-0.01, 0.03]
ile_L_e 0.00229 [0.00229, 0.00229] glyc_S_e 0 [0, 0.0242]
asn_L_e 0.00224 [0.00224, 0.00224] ade_e 0 [-0.01, 0.0196]
phe_L_e 0.00208 [0.00208, 0.00208] amp_e 0 [-0.01, 0.0196]
ser_L_e 0.00168 [0.01, -0.0142] prpp_e 0 [-0.01, 0.0196]
ps_hs_e 0.00151 [0.00142, 0.01] fe2_e 0 [0, 0.01]
lpchol_hs_e 0.00132 [0.00132, 0.0099] fol_c 0 [0, 0.01]
tyr_L_e 0.00128 [0.00128, 0.00128] leuktrB4_e 0 [0, 0.01]
met_L_e 0.00122 [0.00122, 0.00122] leuktrD4_e 0 [0, 0.01]
his_L_e 0.00101 [0.00101, 0.00101] retn_e 0 [0, 0.01]
crvnc_e 0.000979 [0.000979, 0.01] HC01610_e 0 [-0.00208, 0.01]
pe_hs_e 0.000497 [-0.0095, 0.01] cgly_e 0 [-0.01, 0.01]
biomass_other_c 0.000432 [0.000432, 0.000432] fald_e 0 [-0.01, 0.01]
atp_e 0.00043 [0.00043, 0.01] glyc_e 0 [-0.01, 0.01]
uri_e 0.000428 [-0.00957, 0.01] taur_c 0 [-0.01, 0.01]
cys_L_e 0.000373 [0.000373, 0.000373] taur_e 0 [-0.01, 0.01]
cytd_e 0.000312 [0.000312, 0.01] dgtp_m 0 [0, 0.00992]
xmp_e 0.000289 [0.000289, -0.00928] 1glyc_hs_e 0 [0, 0.00988]
inost_e 0.000187 [0.000187, 0.000187] pchol_hs_e 0 [0, 0.00858]
sph1p_e 0.00014 [0.00014, 0.00014] dag_hs_e 0 [-8.5e-05, 0.00849]
pglyc_hs_e 0.000117 [0.000117, 0.01]
trp_L_e 0.000106 [0.000106, 0.000106]
datp_n 0.000105 [0.000105, 0.01]
dttp_n 0.000105 [0.000105, 0.000105]
dgtp_n 7.9e-05 [7.9e-05, 0.01]
arab_L_e 0 [0, 0.01]
fe3_e 0 [0, 0.01]
fol_e 0 [0, 0.01]
leuktrA4_e 0 [0, 0.01]
mag_hs_e 0 [0, 0.01]
retinol_e 0 [0, 0.01]
gthrd_e 0 [-0.00148, 0.01]
HC01609_e 0 [-0.00208, 0.01]
pe_hs_r 0 [-0.0095, 0.01]
utp_e 0 [-0.00957, 0.01]
meoh_e 0 [-0.01, 0.01]
hdca_e 0 [0, 0.00014]
datp_m 0 [0, -0.00989]
===========================
Glucose anaerobic
===========================
Oxigen use o2_e --> 0.0
H2O h2o_e <=> -0.0855259146667
CO2 production co2_e --> 0.008321576
Glucose consumption glc_D_e <-- -1.0
Glutamine consumption gln_L_e --> 0.0
ATP production 1.91671747733
IN FLUXES OUT FLUXES OBJECTIVES
----------------------------------------------- ---------------------------------------- ---------------
id Flux Range id Flux Range DM_atp_c_ 1.92
--------------- -------- -------------------- ---------- -------- ------------------
glc_D_e 1 [1, 1] h_e 2.1 [2.04, 2.27]
h2o_e 0.0855 [0.0428, 0.324] lac_L_e 2.08 [-0.01, 2.12]
akg_e 0.01 [0.01, 0.01] ac_e 0.0317 [0.02, 0.0693]
gam_e 0.01 [0.01, 0.01] nh4_e 0.0287 [0.0287, 0.0531]
glyc3p_e 0.01 [0.01, 0.01] abt_e 0.02 [0, 0.04]
ha_e 0.01 [0.01, 0.01] pyr_e 0.0125 [-0.01, 0.0938]
man_e 0.01 [0.01, 0.01] cit_e 0.0111 [-0.01, 0.0163]
o2s_e 0.01 [0.01, 0.01] co2_e 0.00832 [0, 0.0483]
etoh_e 0.01 [0, 0.01] 5oxpro_e 0.00404 [0, 0.01]
glu_L_e 0.00852 [-0.00148, 0.01] utp_e 0.002 [0.00957, -0.01]
lys_L_e 0.00474 [0.00474, 0.00474] oxa_e 0.0016 [0, 0.0101]
leu_L_e 0.00436 [0.00436, 0.00436] bhb_e 0.0016 [0.0016, 0.00902]
gly_e 0.00431 [0.00431, -0.00578] Rtotal_e 0.00118 [0.00118, 0.0322]
gluala_e 0.00404 [0, 0.01] tmndnc_e 0.000979 [0.000979, 0.01]
pro_L_e 0.0033 [0.0033, 0.0033] for_e 0.000163 [0.000163, 0.0202]
arg_L_e 0.00287 [0.00287, 0.00287] pi_e 0 [0, 0.0838]
val_L_e 0.00282 [0.00282, 0.00282] ppi_e 0 [-0.01, 0.0379]
acac_e 0.00258 [0.00258, 0.01] fum_e 0 [-0.01, 0.0374]
thr_L_e 0.0025 [0.0025, 0.0025] ala_L_e 0 [-0.00909, 0.0302]
uri_e 0.00243 [-0.00957, 0.01] xylt_e 0 [-0.01, 0.03]
ile_L_e 0.00229 [0.00229, 0.00229] glyc_S_e 0 [0, 0.0242]
asn_L_e 0.00224 [0.00224, 0.00224] dcmp_e 0 [-0.01, 0.0196]
phe_L_e 0.00208 [0.00208, 0.00208] ade_e 0 [-0.01, 0.0196]
ser_L_e 0.00177 [0.01, -0.0142] amp_e 0 [-0.01, 0.0196]
4hpro_LT_m 0.0016 [0.0016, 0.00902] prpp_e 0 [-0.01, 0.0196]
ps_hs_e 0.00142 [0.00142, 0.01] dctp_n 0 [-0.01, 0.015]
lpchol_hs_e 0.00132 [0.00132, 0.00239] fe2_e 0 [0, 0.01]
tyr_L_e 0.00128 [0.00128, 0.00128] fol_c 0 [0, 0.01]
met_L_e 0.00122 [0.00122, 0.00122] leuktrB4_e 0 [0, 0.01]
mal_L_e 0.0011 [0.01, -0.0374] leuktrD4_e 0 [0, 0.01]
his_L_e 0.00101 [0.00101, 0.00101] HC01610_e 0 [-0.00208, 0.01]
crvnc_e 0.000979 [0.000979, 0.01] cgly_e 0 [-0.01, 0.01]
pe_hs_e 0.000497 [-0.0095, 0.01] fald_e 0 [-0.01, 0.01]
biomass_other_c 0.000432 [0.000432, 0.000432] glyc_e 0 [-0.01, 0.01]
atp_e 0.00043 [0.00043, 0.01] taur_c 0 [-0.01, 0.01]
cytd_e 0.000388 [0.000312, 0.01] taur_e 0 [-0.01, 0.01]
cys_L_e 0.000373 [0.000373, 0.000373] dgtp_m 0 [0, 0.00992]
xmp_e 0.000289 [0.000289, -0.00928] datp_m 0 [0, 0.00989]
inost_e 0.000187 [0.000187, 0.000187] 1glyc_hs_e 0 [0, 0.00988]
sph1p_e 0.00014 [0.00014, 0.00014] pchol_hs_e 0 [0, 0.00107]
pglyc_hs_e 0.000117 [0.000117, 0.01] retinol_e 0 [0, -0.01]
trp_L_e 0.000106 [0.000106, 0.000106]
datp_n 0.000105 [0.000105, 0.01]
dttp_n 0.000105 [0.000105, 0.000105]
dag_hs_e 8.5e-05 [8.5e-05, -0.00849]
dgtp_n 7.9e-05 [7.9e-05, 0.01]
arab_L_e 0 [0, 0.01]
fe3_e 0 [0, 0.01]
fol_e 0 [0, 0.01]
leuktrA4_e 0 [0, 0.01]
mag_hs_e 0 [0, 0.01]
gthrd_e 0 [-0.00148, 0.01]
HC01609_e 0 [-0.00208, 0.01]
pe_hs_r 0 [-0.0095, 0.01]
meoh_e 0 [-0.01, 0.01]
hdca_e 0 [0, 0.00014]
retn_e 0 [0, -0.01]
lac_D_e 0 [0, -2.13]
# Production of ATP from glucose in anaerobic conditions for Cancer Biopsies
# test for max ATP hydrolysis flux from only glucose
closedModel=model_CancerBiopsy.copy()
closedModel.objective="DM_atp_c_"
for rx in closedModel.exchanges:
rx.upper_bound= 10
rx.lower_bound= -0.01
######################################################################
## Glutamine aerobic
######################################################################
for rx in closedModel.exchanges:
rx.upper_bound= 10
rx.lower_bound= -0.1
closedModel.reactions.EX_h2o_LPAREN_e_RPAREN_.bounds=(-10,10)
closedModel.reactions.EX_h_LPAREN_e_RPAREN_.bounds=(-10,10)
closedModel.reactions.EX_glc_LPAREN_e_RPAREN_.bounds=(0,0)
closedModel.reactions.EX_gln_L_LPAREN_e_RPAREN_.bounds=(-1,-1)
closedModel.reactions.EX_o2_LPAREN_e_RPAREN_.bounds=(-1,-1)
closedModel.reactions.EX_co2_LPAREN_e_RPAREN_.bounds=(0,10)
closedModel.reactions.EX_pi_LPAREN_e_RPAREN_.bounds=(-10,10)
FBA = cobra.flux_analysis.pfba(closedModel)
print("===========================")
print("Glutamine aerobic")
print("===========================")
print("Oxigen use",closedModel.reactions.EX_o2_LPAREN_e_RPAREN_.reaction,FBA["EX_o2_LPAREN_e_RPAREN_"])
print("H2O",closedModel.reactions.EX_h2o_LPAREN_e_RPAREN_.reaction,FBA["EX_h2o_LPAREN_e_RPAREN_"])
print("CO2 production",closedModel.reactions.EX_co2_LPAREN_e_RPAREN_.reaction,FBA["EX_co2_LPAREN_e_RPAREN_"])
print("Glucose consumption",closedModel.reactions.EX_glc_LPAREN_e_RPAREN_.reaction,FBA["EX_glc_LPAREN_e_RPAREN_"])
print("Glutamine consumption",closedModel.reactions.EX_gln_L_LPAREN_e_RPAREN_.reaction,FBA["EX_gln_L_LPAREN_e_RPAREN_"])
print("ATP production",FBA["DM_atp_c_"])
closedModel.summary(fva=True)
######################################################################
## Glutamine anaerobic
######################################################################
closedModel.reactions.EX_h2o_LPAREN_e_RPAREN_.bounds=(-10,10)
closedModel.reactions.EX_h_LPAREN_e_RPAREN_.bounds=(-10,10)
closedModel.reactions.EX_glc_LPAREN_e_RPAREN_.bounds=(0,0)
closedModel.reactions.EX_gln_L_LPAREN_e_RPAREN_.bounds=(-1,-1)
closedModel.reactions.EX_o2_LPAREN_e_RPAREN_.bounds=(0,0)
closedModel.reactions.EX_co2_LPAREN_e_RPAREN_.bounds=(0,10)
closedModel.reactions.EX_pi_LPAREN_e_RPAREN_.bounds=(-10,10)
FBA = cobra.flux_analysis.pfba(closedModel)
print("===========================")
print("Glutamine anaerobic")
print("===========================")
print("Oxigen use",closedModel.reactions.EX_o2_LPAREN_e_RPAREN_.reaction,FBA["EX_o2_LPAREN_e_RPAREN_"])
print("H2O",closedModel.reactions.EX_h2o_LPAREN_e_RPAREN_.reaction,FBA["EX_h2o_LPAREN_e_RPAREN_"])
print("CO2 production",closedModel.reactions.EX_co2_LPAREN_e_RPAREN_.reaction,FBA["EX_co2_LPAREN_e_RPAREN_"])
print("Glucose consumption",closedModel.reactions.EX_glc_LPAREN_e_RPAREN_.reaction,FBA["EX_glc_LPAREN_e_RPAREN_"])
print("Glutamine consumption",closedModel.reactions.EX_gln_L_LPAREN_e_RPAREN_.reaction,FBA["EX_gln_L_LPAREN_e_RPAREN_"])
print("ATP production",FBA["DM_atp_c_"])
closedModel.summary(fva=True)===========================
Glutamine aerobic
===========================
Oxigen use o2_e <-- -1.0
H2O h2o_e <=> -0.1
CO2 production co2_e --> 0.0
Glucose consumption glc_D_e --> 0.0
Glutamine consumption gln_L_e <-- -1.0
ATP production 1.1342295279
IN FLUXES OUT FLUXES OBJECTIVES
----------------------------------------------- ------------------------------------------- ---------------
id Flux Range id Flux Range DM_atp_c_ 1.13
--------------- -------- -------------------- ----------- -------- --------------------
gln_L_e 1 [1, 1] nh4_e 1.2 [1.2, 1.55]
o2_e 1 [1, 1] h_e 0.97 [-0.988, 1.4]
3mob_e 0.1 [0.1, 0.1] cit_e 0.688 [-0.1, 0.951]
bhb_e 0.1 [0.1, 0.1] ala_L_e 0.654 [0.193, 0.768]
chol_e 0.1 [0.1, 0.1] pro_L_e 0.566 [0.435, 1.32]
cys_L_e 0.1 [0.1, 0.1] pi_e 0.315 [0.315, 0.815]
din_e 0.1 [0.1, 0.1] ac_e 0.174 [0.174, 0.274]
fe2_e 0.1 [0.1, 0.1] urate_e 0.174 [0.174, 0.174]
gam_e 0.1 [0.1, 0.1] acac_e 0.1 [0.1, 0.1]
glyc_e 0.1 [0.1, 0.1] fald_e 0.1 [0.1, 0.1]
lac_D_e 0.1 [0.1, 0.1] fe3_e 0.1 [0.1, 0.1]
lac_L_e 0.1 [0.1, 0.1] vacc_e 0.1 [0.1, 0.1]
meoh_e 0.1 [0.1, 0.1] taur_c 0.1 [-0.1, 0.1]
o2s_e 0.1 [0.1, 0.1] glyb_e 0.0987 [0.0987, 0.0987]
ocdca_e 0.1 [0.1, 0.1] dag_hs_e 0.0985 [0.0985, 0.0985]
ppa_e 0.1 [0.1, 0.1] gly_e 0.0957 [0.0957, 0.0957]
ps_hs_e 0.1 [0.1, 0.1] uri_e 0.0736 [0.0736, 0.274]
ser_L_e 0.1 [0.1, 0.1] Lcystin_c 0.0498 [0.0498, 0.0498]
val_L_e 0.1 [0.1, 0.1] akg_e 0.0315 [-0.1, 0.425]
xylt_e 0.1 [0.1, 0.1] pyr_e 0.0138 [-0.1, 0.475]
taur_e 0.1 [0.1, -0.1] retn_e 0.0104 [0, 0.1]
h2o_e 0.1 [0.963, -1] for_e 0.000163 [0.000163, 0.000163]
gsn_e 0.0746 [0.0746, 0.0746] co2_e 0 [0, 1.5]
dctp_n 0.0744 [0.0744, 0.0744] ppi_e 0 [-0.1, 0.2]
retinol_e 0.0104 [0, 0.1] 3bcrn_e 0 [0, 0.1]
lys_L_e 0.00474 [0.00474, 0.00474] ivcrn_e 0 [0, 0.1]
leu_L_e 0.00436 [-0.0956, 0.1] lpchol_hs_e 0 [0, 0.1]
arg_L_e 0.00287 [0.00287, 0.00287] ribflv_e 0 [0, 0.1]
thr_L_e 0.0025 [0.0025, 0.0025] HC01609_e 0 [-0.1, 0.1]
ile_L_e 0.00229 [0.00229, 0.1] ade_e 0 [-0.1, 0.1]
asn_L_e 0.00224 [0.00224, 0.00224] amp_e 0 [-0.1, 0.1]
phe_L_e 0.00208 [0.00208, 0.00208] prpp_e 0 [-0.1, 0.1]
tyr_L_e 0.00128 [0.00128, 0.00128] sprm_c 0 [-0.1, 0.1]
met_L_e 0.00122 [0.00122, 0.00122] sprm_e 0 [-0.1, 0.1]
his_L_e 0.00101 [0.00101, 0.00101] ump_e 0 [-0.1, 0.1]
pe_hs_e 0.000497 [-0.0995, 0.1] crn_e 0 [0, -0.1]
hdca_e 0.00049 [0.00049, 0.00063]
biomass_other_c 0.000432 [0.000432, 0.000432]
adn_e 0.00043 [0.00043, 0.00043]
inost_e 0.000187 [0.000187, 0.000187]
sph1p_e 0.00014 [0.00014, 0.00014]
Rtotal_e 0.00014 [0.00014, -0.1]
pglyc_hs_e 0.000117 [0.000117, 0.000117]
trp_L_e 0.000106 [0.000106, 0.000106]
datp_n 0.000105 [0.000105, 0.000105]
dttp_n 0.000105 [0.000105, 0.000105]
dgtp_n 7.9e-05 [7.9e-05, 7.9e-05]
cytd_e 5.4e-05 [5.4e-05, 5.4e-05]
2hb_e 0 [0, 0.1]
asp_L_e 0 [0, 0.1]
etoh_e 0 [0, 0.1]
fmn_e 0 [0, 0.1]
pchol_hs_e 0 [0, 0.1]
utp_e 0 [0, 0.1]
4mop_e 0 [-0.0956, 0.1]
pe_hs_r 0 [-0.0995, 0.1]
HC01610_e 0 [-0.1, 0.1]
===========================
Glutamine anaerobic
===========================
Oxigen use o2_e --> 0.0
H2O h2o_e <=> 0.153133899429
CO2 production co2_e --> 0.0
Glucose consumption glc_D_e --> 0.0
Glutamine consumption gln_L_e <-- -1.0
ATP production 0.133201932762
IN FLUXES OUT FLUXES OBJECTIVES
----------------------------------------------- ------------------------------------------- ----------------
id Flux Range id Flux Range DM_atp_c_ 0.133
--------------- -------- -------------------- ----------- -------- --------------------
gln_L_e 1 [1, 1] nh4_e 1.1 [1.06, 1.53]
bhb_e 0.1 [0.1, 0.1] pro_L_e 0.61 [0.575, 0.918]
cys_L_e 0.1 [0.1, 0.1] ala_L_e 0.565 [0.193, 0.665]
gam_e 0.1 [0.1, 0.1] akg_e 0.457 [0.0783, 0.562]
glyc_e 0.1 [0.1, 0.1] h2o_e 0.153 [0.446, -0.59]
lac_D_e 0.1 [0.1, 0.1] acac_e 0.1 [0.1, 0.1]
lac_L_e 0.1 [0.1, 0.1] fald_e 0.1 [0.1, 0.1]
meoh_e 0.1 [0.1, 0.1] dag_hs_e 0.0985 [0.0985, 0.0985]
o2s_e 0.1 [0.1, 0.1] gly_e 0.0957 [0.0957, 0.0957]
ps_hs_e 0.1 [0.1, 0.1] cit_e 0.0689 [-0.1, 0.258]
ser_L_e 0.1 [0.1, 0.1] HC01609_e 0.0633 [-0.1, 0.1]
xylt_e 0.1 [0.1, 0.1] Lcystin_c 0.0498 [0.0498, 0.0498]
asp_L_e 0.1 [0.0381, 0.1] 3bcrn_e 0.0381 [0.0381, 0.1]
HC01610_e 0.0633 [0.1, -0.1] dctp_n 0.0273 [0.0273, 0.0273]
ppa_e 0.0474 [0.0474, 0.0474] pi_e 0.00978 [0.00978, 0.51]
crn_e 0.0381 [0.0381, 0.1] for_e 0.000163 [0.000163, 0.000163]
h_e 0.031 [-0.283, 1.22] co2_e 0 [0, 0.946]
cytd_e 0.0277 [0.0277, 0.0277] pyr_e 0 [-0.1, 0.372]
lys_L_e 0.00474 [0.00474, 0.00474] ppi_e 0 [-0.1, 0.2]
4mop_e 0.00436 [-0.0956, 0.1] lpchol_hs_e 0 [0, 0.1]
arg_L_e 0.00287 [0.00287, 0.00287] ribflv_e 0 [0, 0.1]
3mob_e 0.00282 [-0.0972, 0.1] ade_e 0 [-0.1, 0.1]
thr_L_e 0.0025 [0.0025, 0.0025] amp_e 0 [-0.1, 0.1]
ile_L_e 0.00229 [0.00229, 0.00229] prpp_e 0 [-0.1, 0.1]
asn_L_e 0.00224 [0.00224, 0.00224] sprm_c 0 [-0.1, 0.1]
phe_L_e 0.00208 [0.00208, 0.00208] taur_c 0 [-0.1, 0.1]
chol_e 0.00132 [0.00132, 0.00132] taur_e 0 [-0.1, 0.1]
tyr_L_e 0.00128 [0.00128, 0.00128] ump_e 0 [-0.1, 0.1]
met_L_e 0.00122 [0.00122, 0.00122] ac_e 0 [0, 0.0619]
his_L_e 0.00101 [0.00101, 0.00101] ivcrn_e 0 [0, 0.0619]
pe_hs_e 0.000497 [-0.0995, 0.1] etoh_e 0 [0, -0.0619]
biomass_other_c 0.000432 [0.000432, 0.000432]
adn_e 0.00043 [0.00043, 0.00043]
uri_e 0.000428 [0.000428, -0.2]
gsn_e 0.000289 [0.000289, 0.000289]
inost_e 0.000187 [0.000187, 0.000187]
sph1p_e 0.00014 [0.00014, 0.00014]
Rtotal_e 0.00014 [0.00014, -0.1]
pglyc_hs_e 0.000117 [0.000117, 0.000117]
trp_L_e 0.000106 [0.000106, 0.000106]
datp_n 0.000105 [0.000105, 0.000105]
dttp_n 0.000105 [0.000105, 0.000105]
dgtp_n 7.9e-05 [7.9e-05, 7.9e-05]
fmn_e 0 [0, 0.1]
pchol_hs_e 0 [0, 0.1]
utp_e 0 [0, 0.1]
leu_L_e 0 [-0.0956, 0.1]
val_L_e 0 [-0.0972, 0.1]
pe_hs_r 0 [-0.0995, 0.1]
sprm_e 0 [-0.1, 0.1]
retinol_e 0 [0, 0.0619]
hdca_e 0 [0, 0.00014]
retn_e 0 [0, -0.0619]
closedModel=model_NormalBiopsy.copy() closedModel.objective="DM_atp_c_"
for rx in closedModel.exchanges: rx.upper_bound= 10 rx.lower_bound= -0.01
######################################################################
######################################################################
for rx in closedModel.exchanges: rx.upper_bound= 10 rx.lower_bound= -0.1
closedModel.reactions.EX_h2o_LPAREN_e_RPAREN_.bounds=(-10,10) closedModel.reactions.EX_h_LPAREN_e_RPAREN_.bounds=(-10,10) closedModel.reactions.EX_glc_LPAREN_e_RPAREN_.bounds=(0,0) closedModel.reactions.EX_gln_L_LPAREN_e_RPAREN_.bounds=(-1,-1) closedModel.reactions.EX_o2_LPAREN_e_RPAREN_.bounds=(-1,-1) closedModel.reactions.EX_co2_LPAREN_e_RPAREN_.bounds=(0,10) closedModel.reactions.EX_pi_LPAREN_e_RPAREN_.bounds=(-10,10)
FBA = cobra.flux_analysis.pfba(closedModel) print("===========================") print("Glutamine aerobic") print("===========================") print("Oxigen use",closedModel.reactions.EX_o2_LPAREN_e_RPAREN_.reaction,FBA["EX_o2_LPAREN_e_RPAREN_"]) print("H2O",closedModel.reactions.EX_h2o_LPAREN_e_RPAREN_.reaction,FBA["EX_h2o_LPAREN_e_RPAREN_"]) print("CO2 production",closedModel.reactions.EX_co2_LPAREN_e_RPAREN_.reaction,FBA["EX_co2_LPAREN_e_RPAREN_"]) print("Glucose consumption",closedModel.reactions.EX_glc_LPAREN_e_RPAREN_.reaction,FBA["EX_glc_LPAREN_e_RPAREN_"]) print("Glutamine consumption",closedModel.reactions.EX_gln_L_LPAREN_e_RPAREN_.reaction,FBA["EX_gln_L_LPAREN_e_RPAREN_"]) print("ATP production",FBA["DM_atp_c_"])
closedModel.summary(fva=True)
######################################################################
######################################################################
closedModel.reactions.EX_h2o_LPAREN_e_RPAREN_.bounds=(-10,10) closedModel.reactions.EX_h_LPAREN_e_RPAREN_.bounds=(-10,10) closedModel.reactions.EX_glc_LPAREN_e_RPAREN_.bounds=(0,0) closedModel.reactions.EX_gln_L_LPAREN_e_RPAREN_.bounds=(-1,-1) closedModel.reactions.EX_o2_LPAREN_e_RPAREN_.bounds=(0,0) closedModel.reactions.EX_co2_LPAREN_e_RPAREN_.bounds=(0,10) closedModel.reactions.EX_pi_LPAREN_e_RPAREN_.bounds=(-10,10)
FBA = cobra.flux_analysis.pfba(closedModel)
print("===========================") print("Glutamine anaerobic") print("===========================") print("Oxigen use",closedModel.reactions.EX_o2_LPAREN_e_RPAREN_.reaction,FBA["EX_o2_LPAREN_e_RPAREN_"]) print("H2O",closedModel.reactions.EX_h2o_LPAREN_e_RPAREN_.reaction,FBA["EX_h2o_LPAREN_e_RPAREN_"]) print("CO2 production",closedModel.reactions.EX_co2_LPAREN_e_RPAREN_.reaction,FBA["EX_co2_LPAREN_e_RPAREN_"]) print("Glucose consumption",closedModel.reactions.EX_glc_LPAREN_e_RPAREN_.reaction,FBA["EX_glc_LPAREN_e_RPAREN_"]) print("Glutamine consumption",closedModel.reactions.EX_gln_L_LPAREN_e_RPAREN_.reaction,FBA["EX_gln_L_LPAREN_e_RPAREN_"]) print("ATP production",FBA["DM_atp_c_"])
closedModel.summary(fva=True)
def model_create(rec, conf, nsize, m, pf):
opt=CORDA(model=rec, confidence=conf, n=nsize, met_prod=m, penalty_factor=pf )
opt.build()
return(opt)%%time
from multiprocessing import Pool
from corda import CORDA
pool = Pool()
res1=pool.apply_async(model_create, [Recon2, conf_CancerBiopsy, 5, metas ,100] )
res2=pool.apply_async(model_create, [Recon2, conf_CancerBiopsy, 5, metas ,500] )
res3=pool.apply_async(model_create, [Recon2, conf_CancerBiopsy, 5, metas ,1000] )
res4=pool.apply_async(model_create, [Recon2, conf_CancerBiopsy, 5, metas ,2500] )
res5=pool.apply_async(model_create, [Recon2, conf_CancerBiopsy, 5, metas ,5000] )
res6=pool.apply_async(model_create, [Recon2, conf_NormalBiopsy, 5, metas ,100] )
res7=pool.apply_async(model_create, [Recon2, conf_NormalBiopsy, 5, metas ,500] )
res8=pool.apply_async(model_create, [Recon2, conf_NormalBiopsy, 5, metas ,1000] )
res9=pool.apply_async(model_create, [Recon2, conf_NormalBiopsy, 5, metas ,2500] )
res0=pool.apply_async(model_create, [Recon2, conf_NormalBiopsy, 5, metas ,5000] )
opt_CancerBiopsy1=res1.get()
opt_CancerBiopsy2=res2.get()
opt_CancerBiopsy3=res3.get()
opt_CancerBiopsy4=res4.get()
opt_CancerBiopsy5=res5.get()
opt_NormalBiopsy1=res6.get()
opt_NormalBiopsy2=res7.get()
opt_NormalBiopsy3=res8.get()
opt_NormalBiopsy4=res9.get()
opt_NormalBiopsy5=res0.get() CPU times: user 1min 2s, sys: 9.83 s, total: 1min 12s
Wall time: 29min 32s
model_CancerBiopsy1=opt_CancerBiopsy1.cobra_model(name="Cancer1")
print(model_CancerBiopsy1.optimize())
model_CancerBiopsy2=opt_CancerBiopsy2.cobra_model(name="Cancer2")
print(model_CancerBiopsy2.optimize())
model_CancerBiopsy3=opt_CancerBiopsy3.cobra_model(name="Cancer3")
print(model_CancerBiopsy3.optimize())
model_CancerBiopsy4=opt_CancerBiopsy4.cobra_model(name="Cancer4")
print(model_CancerBiopsy4.optimize())
model_CancerBiopsy5=opt_CancerBiopsy5.cobra_model(name="Cancer5")
print(model_CancerBiopsy5.optimize())<Solution 0.029 at 0x7f8066914c50>
<Solution 0.033 at 0x7f8051d085c0>
<Solution 0.033 at 0x7f8064580208>
<Solution 0.033 at 0x7f8052a9bf28>
<Solution 0.033 at 0x7f805d8331d0>
model_NormalBiopsy1=opt_NormalBiopsy1.cobra_model(name="Norm1")
print(model_NormalBiopsy1.optimize())
model_NormalBiopsy2=opt_NormalBiopsy2.cobra_model(name="Norm2")
print(model_NormalBiopsy2.optimize())
model_NormalBiopsy3=opt_NormalBiopsy3.cobra_model(name="Norm3")
print(model_NormalBiopsy3.optimize())
model_NormalBiopsy4=opt_NormalBiopsy4.cobra_model(name="Norm4")
print(model_NormalBiopsy4.optimize())
model_NormalBiopsy5=opt_NormalBiopsy5.cobra_model(name="Norm5")
print(model_NormalBiopsy5.optimize())<Solution 0.022 at 0x7f8094c2eba8>
<Solution 0.022 at 0x7f8078dece48>
<Solution 0.022 at 0x7f8072053978>
<Solution 0.022 at 0x7f8085ef2be0>
<Solution 0.022 at 0x7f807bb0f390>
model_CancerBiopsy1.summary(fva=True)IN FLUXES OUT FLUXES OBJECTIVES
----------------------------------------------- ------------------------------------------- -----------------------
id Flux Range id Flux Range biomass_reac... 0.0291
--------------- -------- -------------------- --------------- -------- ----------------
glc_D_e 0.289 [0.159, 1] h_e 0.6 [-0.0997, 3.29]
o2_e 0.0594 [-0.0065, 1] lac_L_e 0.503 [-0.09, 2.71]
gln_L_e 0.037 [0.09, -0.167] pyr_e 0.049 [-0.012, 1.42]
Lcystin_c 0.0236 [-0.00532, 0.024] cys_L_e 0.0459 [-0.012, 0.0466]
val_L_e 0.0229 [-0.00174, 0.03] nh4_e 0.0396 [-0.012, 0.502]
lys_L_e 0.0172 [0.0172, 0.0292] ala_L_e 0.0252 [-0.0147, 0.294]
gly_e 0.0157 [0.03, -0.267] cit_e 0.0187 [-0.012, 0.361]
pro_L_e 0.012 [0.012, 0.012] h2o_e 0.015 [-0.371, 1.42]
leu_L_e 0.012 [0.00387, 0.012] co2_e 0.015 [0, 1.4]
crn_e 0.012 [0, 0.012] dcmp_e 0.0108 [-0.012, 0.076]
gam_e 0.012 [0, 0.012] uri_e 0.0102 [-0.012, 0.076]
o2s_e 0.012 [0, 0.012] pi_e 0.00699 [-0.04, 0.135]
dctp_n 0.012 [0.012, -0.0465] 3ivcrn_e 0.00681 [0, 0.012]
cytd_e 0.012 [0.012, -0.076] dag_hs_e 0.00652 [-0.012, 0.184]
ps_hs_e 0.012 [0.012, -0.156] 3deccrn_e 0.00519 [0, 0.012]
ser_L_e 0.012 [0.012, -0.285] ac_e 0.000938 [-0.012, 0.516]
arg_L_e 0.0105 [0.0105, 0.0105] urate_e 0.000938 [0, 0.0739]
thr_L_e 0.0091 [0.0091, 0.012] for_e 0.000594 [-0.012, 0.102]
ile_L_e 0.00832 [0.00832, 0.012] fe3_e 0 [-0.012, 0.545]
asn_L_e 0.00813 [0.00813, 0.012] oxa_e 0 [0, 0.465]
phe_L_e 0.00755 [0.00755, 0.012] vacc_e 0 [0, 0.453]
arachd_e 0.00519 [0, 0.012] elaid_e 0 [0, 0.449]
chol_e 0.0048 [0.012, -0.0134] no_e 0 [0, 0.448]
tyr_L_e 0.00464 [0.00464, 0.012] gal_e 0 [0, 0.42]
met_L_e 0.00445 [0.00445, 0.012] xylt_e 0 [-0.012, 0.347]
4mop_e 0.00387 [0.00387, 0.012] akg_e 0 [-0.012, 0.344]
his_L_e 0.00368 [0.00368, 0.012] ocdcea_e 0 [0, 0.333]
gsn_e 0.00199 [-0.0109, 0.012] hdcea_e 0 [0, 0.328]
pe_hs_e 0.00181 [0.012, -0.159] acmana_e 0 [0, 0.305]
biomass_other_c 0.00157 [0.00157, 0.00157] glyc_S_e 0 [0, 0.297]
adn_e 0.00156 [0.00911, -0.0214] glyc_e 0 [-0.21, 0.297]
inost_e 0.000678 [0.000678, 0.000678] ha_pre1_e 0 [0, 0.195]
hdca_e 0.000509 [-0.031, 0.3] nrvnc_e 0 [0, 0.178]
sph1p_e 0.000509 [0.012, -0.163] ethamp_r 0 [0, 0.17]
pglyc_hs_e 0.000424 [0.000424, 0.000424] pe_hs_r 0 [-0.012, 0.159]
trp_L_e 0.000387 [0.000387, 0.012] thymd_e 0 [-0.012, 0.1]
datp_n 0.000384 [0.000384, 0.000384] ha_e 0 [-0.012, 0.0908]
dttp_n 0.000381 [0.000381, -0.0581] ppa_e 0 [-0.012, 0.067]
dgtp_n 0.000288 [0.000288, 0.000288] clpnd_e 0 [0, 0.06]
fe2_e 0 [-0.012, 0.545] dlnlcg_e 0 [0, 0.06]
ocdca_e 0 [0, 0.07] eicostet_e 0 [0, 0.06]
lnlc_e 0 [0, 0.06] lnlnca_e 0 [0, 0.06]
gthrd_e 0 [-0.0586, 0.06] lnlncg_e 0 [0, 0.06]
utp_e 0 [0, 0.02] so4_e 0 [0, 0.0586]
3hpvs_e 0 [0, 0.012] taur_c 0 [0, 0.0586]
4hpro_LT_m 0 [0, 0.012] taur_e 0 [0, 0.0586]
amp_e 0 [0, 0.012] tchola_e 0 [0, 0.0564]
arab_L_e 0 [0, 0.012] chsterol_e 0 [0, 0.0545]
asp_L_e 0 [0, 0.012] 4mptnl_e 0 [0, 0.0532]
crvnc_e 0 [0, 0.012] aprgstrn_e 0 [0, 0.0532]
dcyt_e 0 [0, 0.012] 5adtststerone_e 0 [0, 0.0516]
din_e 0 [0, 0.012] andrstrn_e 0 [0, 0.0516]
dopa_e 0 [0, 0.012] gchola_e 0 [-0.012, 0.0485]
etoh_e 0 [0, 0.012] fuc13galacgl... 0 [0, 0.048]
fmn_e 0 [0, 0.012] fuc14galacgl... 0 [0, 0.048]
gluala_e 0 [0, 0.012] 5adtststeron... 0 [0, 0.0459]
leuktrA4_e 0 [0, 0.012] andrstrnglc_e 0 [0, 0.0459]
n2m2nmasn_e 0 [0, 0.012] tststeroneglc_e 0 [0, 0.0458]
orn_e 0 [0, 0.012] fuc_L_e 0 [0, 0.0364]
ptrc_e 0 [0, 0.012] man_e 0 [-0.012, 0.036]
ptvstlac_e 0 [0, 0.012] Rtotal_e 0 [0, 0.025]
retn_e 0 [0, 0.012] lpchol_hs_e 0 [0, 0.025]
spmd_e 0 [0, 0.012] pchol_hs_e 0 [0, 0.025]
nac_e 0 [-0.0116, 0.012] gthox_e 0 [0, 0.024]
fald_e 0 [-0.012, 0.024]
meoh_e 0 [-0.012, 0.024]
1mncam_e 0 [0, 0.0236]
ppi_e 0 [0, 0.02]
ump_e 0 [0, 0.02]
3mob_e 0 [-0.012, 0.0197]
fucfucfucgal... 0 [0, 0.016]
13_cis_retng... 0 [0, 0.012]
34dhoxpeg_e 0 [0, 0.012]
3bcrn_e 0 [0, 0.012]
3ddcrn_e 0 [0, 0.012]
3hdececrn_e 0 [0, 0.012]
3hexdcrn_e 0 [0, 0.012]
3hpvstet_e 0 [0, 0.012]
3octdec2crn_e 0 [0, 0.012]
3octdeccrn_e 0 [0, 0.012]
3octdece1crn_e 0 [0, 0.012]
3tdcrn_e 0 [0, 0.012]
3tetd7ecoacrn_e 0 [0, 0.012]
3thexddcoacrn_e 0 [0, 0.012]
3ttetddcoacrn_e 0 [0, 0.012]
4abutn_e 0 [0, 0.012]
Asn_X_Ser_Thr_l 0 [0, 0.012]
CE1940_e 0 [0, 0.012]
abt_e 0 [0, 0.012]
ade_e 0 [0, 0.012]
adrn_e 0 [0, 0.012]
c5dc_e 0 [0, 0.012]
c6crn_e 0 [0, 0.012]
leuktrB4_e 0 [0, 0.012]
leuktrD4_e 0 [0, 0.012]
n5m2masn_g 0 [0, 0.012]
prpp_e 0 [0, 0.012]
ptvst_e 0 [0, 0.012]
retnglc_e 0 [0, 0.012]
ribflv_e 0 [0, 0.012]
HC01609_e 0 [-0.012, 0.012]
HC01610_e 0 [-0.012, 0.012]
acac_e 0 [-0.012, 0.012]
bhb_e 0 [-0.012, 0.012]
anth_c 0 [0, 0.0116]
3mlda_e 0 [0, 0.00832]
ivcrn_e 0 [0, 0.00813]
5mta_e 0 [0, 0.00755]
sprm_c 0 [0, 0.00755]
sprm_e 0 [0, 0.00755]
4hphac_e 0 [0, 0.00736]
q10h2_e 0 [0, 0.00736]
bilglcur_e 0 [0, 0.00547]
co_e 0 [0, 0.00547]
pheme_e 0 [0, 0.00547]
pheacgln_e 0 [0, 0.00445]
2hb_e 0 [0.0029, -0.012]
model_CancerBiopsy2.summary(fva=True)IN FLUXES OUT FLUXES OBJECTIVES
----------------------------------------------- ------------------------------------------- -----------------------
id Flux Range id Flux Range biomass_reac... 0.0334
--------------- -------- -------------------- --------------- -------- ----------------
glc_D_e 0.362 [0.22, 1] h_e 0.698 [-0.0486, 3.2]
o2_e 0.0845 [-0.0058, 1] lac_L_e 0.627 [-0.09, 2.67]
Lcystin_c 0.024 [-0.00522, 0.024] co2_e 0.0503 [0, 1.34]
pi_e 0.0208 [0.04, -0.0836] h2o_e 0.0503 [-0.37, 1.29]
lys_L_e 0.0198 [0.0198, 0.03] pyr_e 0.0474 [-0.012, 1.26]
gly_e 0.018 [0.03, -0.269] cys_L_e 0.0339 [-0.012, 0.0464]
gthrd_e 0.012 [-0.0584, 0.06] glyc_S_e 0.016 [0, 0.299]
arg_L_e 0.012 [0.012, 0.012] ac_e 0.0129 [-0.012, 0.473]
4mop_e 0.012 [0.00622, 0.012] so4_e 0.0126 [0, 0.0584]
asp_L_e 0.012 [0, 0.012] urate_e 0.012 [0, 0.072]
crn_e 0.012 [0, 0.012] 34dhoxpeg_e 0.012 [0, 0.012]
din_e 0.012 [0, 0.012] leuktrD4_e 0.012 [0, 0.012]
dopa_e 0.012 [0, 0.012] 3bcrn_e 0.00996 [0, 0.012]
leuktrA4_e 0.012 [0, 0.012] uri_e 0.00891 [-0.012, 0.0517]
o2s_e 0.012 [0, 0.012] dag_hs_e 0.00665 [-0.012, 0.183]
3mob_e 0.012 [0.012, -0.0182] ptvst_e 0.00309 [0, 0.012]
cytd_e 0.012 [0.012, -0.0517] 3deccrn_e 0.00204 [0, 0.012]
ps_hs_e 0.012 [0.012, -0.112] lac_D_e 0.001 [-0.001, 0.001]
ser_L_e 0.012 [0.012, -0.287] for_e 0.000681 [-0.012, 0.099]
gln_L_e 0.0118 [0.09, -0.13] cit_e 0.000222 [-0.012, 0.327]
thr_L_e 0.0104 [0.0104, 0.012] fe3_e 0 [-0.012, 0.545]
ile_L_e 0.00956 [0.00956, 0.012] vacc_e 0 [0, 0.449]
asn_L_e 0.00933 [0.00933, 0.012] oxa_e 0 [0, 0.448]
ppa_e 0.00888 [0.012, -0.0616] elaid_e 0 [0, 0.43]
phe_L_e 0.00867 [0.00867, 0.012] nh4_e 0 [-0.012, 0.427]
leu_L_e 0.00622 [0.00622, 0.012] gal_e 0 [0, 0.39]
chol_e 0.00552 [-0.0116, 0.012] no_e 0 [0, 0.385]
tyr_L_e 0.00533 [0.00533, 0.012] hdcea_e 0 [0, 0.326]
met_L_e 0.00511 [0.00511, 0.012] ocdcea_e 0 [0, 0.31]
val_L_e 0.00458 [-0.000222, 0.03] glyc_e 0 [-0.21, 0.299]
his_L_e 0.00422 [0.00422, 0.012] ala_L_e 0 [-0.0169, 0.294]
ptvstlac_e 0.00309 [0, 0.012] pro_L_e 0 [-0.012, 0.287]
pe_hs_e 0.00302 [0.012, -0.112] acmana_e 0 [0, 0.287]
arachd_e 0.00204 [0, 0.012] ha_pre1_e 0 [0, 0.184]
gam_e 0.00184 [0, 0.012] nrvnc_e 0 [0, 0.165]
biomass_other_c 0.0018 [0.0018, 0.0018] ethamp_r 0 [0, 0.124]
adn_e 0.00179 [0.00868, -0.021] pe_hs_r 0 [-0.012, 0.112]
gsn_e 0.00121 [-0.0108, 0.012] ha_e 0 [-0.012, 0.0852]
inost_e 0.000779 [0.000779, 0.000779] thymd_e 0 [-0.012, 0.0757]
hdca_e 0.000584 [-0.0291, 0.3] clpnd_e 0 [0, 0.06]
sph1p_e 0.000584 [0.012, -0.112] dlnlcg_e 0 [0, 0.06]
pglyc_hs_e 0.000487 [0.000487, 0.000487] eicostet_e 0 [0, 0.06]
trp_L_e 0.000444 [0.000444, 0.012] lnlnca_e 0 [0, 0.06]
datp_n 0.00044 [0.00044, 0.00044] lnlncg_e 0 [0, 0.06]
dttp_n 0.000437 [0.000437, -0.0408] taur_c 0 [0, 0.0584]
dgtp_n 0.000331 [0.000331, 0.000331] taur_e 0 [0, 0.0584]
dctp_n 0.000315 [0.000315, 0.000315] tchola_e 0 [0, 0.0536]
fe2_e 0 [-0.012, 0.545] chsterol_e 0 [0, 0.0513]
ocdca_e 0 [0, 0.07] 4mptnl_e 0 [0, 0.0501]
lnlc_e 0 [0, 0.06] aprgstrn_e 0 [0, 0.0501]
utp_e 0 [0, 0.02] 5adtststerone_e 0 [0, 0.0486]
3hpvs_e 0 [0, 0.012] andrstrn_e 0 [0, 0.0486]
4hpro_LT_m 0 [0, 0.012] fuc13galacgl... 0 [0, 0.048]
amp_e 0 [0, 0.012] fuc14galacgl... 0 [0, 0.048]
arab_L_e 0 [0, 0.012] gchola_e 0 [-0.012, 0.0456]
crvnc_e 0 [0, 0.012] 5adtststeron... 0 [0, 0.0431]
dcyt_e 0 [0, 0.012] andrstrnglc_e 0 [0, 0.0431]
etoh_e 0 [0, 0.012] tststeroneglc_e 0 [0, 0.0429]
fmn_e 0 [0, 0.012] man_e 0 [-0.012, 0.036]
gluala_e 0 [0, 0.012] fuc_L_e 0 [0, 0.0338]
n2m2nmasn_e 0 [0, 0.012] 13_cis_retng... 0 [0, 0.024]
ptrc_e 0 [0, 0.012] gthox_e 0 [0, 0.024]
retinol_e 0 [0, 0.012] retnglc_e 0 [0, 0.024]
spmd_e 0 [0, 0.012] fald_e 0 [-0.012, 0.024]
2hb_e 0 [-0.00156, 0.012] meoh_e 0 [-0.012, 0.024]
nac_e 0 [-0.0116, 0.012] 1mncam_e 0 [0, 0.0236]
xylt_e 0 [0.012, -0.319] glyb_e 0 [0, 0.0235]
Rtotal_e 0 [0, 0.0231]
lpchol_hs_e 0 [0, 0.0231]
pchol_hs_e 0 [0, 0.0231]
ppi_e 0 [0, 0.02]
ump_e 0 [0, 0.02]
fucfucfucgal... 0 [0, 0.016]
3ddcrn_e 0 [0, 0.012]
3hdececrn_e 0 [0, 0.012]
3hexdcrn_e 0 [0, 0.012]
3hpvstet_e 0 [0, 0.012]
3ivcrn_e 0 [0, 0.012]
3octdec2crn_e 0 [0, 0.012]
3octdeccrn_e 0 [0, 0.012]
3octdece1crn_e 0 [0, 0.012]
3tdcrn_e 0 [0, 0.012]
3tetd7ecoacrn_e 0 [0, 0.012]
3thexddcoacrn_e 0 [0, 0.012]
3ttetddcoacrn_e 0 [0, 0.012]
4abutn_e 0 [0, 0.012]
Asn_X_Ser_Thr_l 0 [0, 0.012]
CE1940_e 0 [0, 0.012]
abt_e 0 [0, 0.012]
ade_e 0 [0, 0.012]
adrn_e 0 [0, 0.012]
c6crn_e 0 [0, 0.012]
leuktrB4_e 0 [0, 0.012]
n5m2masn_g 0 [0, 0.012]
prpp_e 0 [0, 0.012]
ribflv_e 0 [0, 0.012]
HC01609_e 0 [-0.012, 0.012]
HC01610_e 0 [-0.012, 0.012]
acac_e 0 [-0.012, 0.012]
bhb_e 0 [-0.012, 0.012]
retn_e 0 [-0.012, 0.012]
anth_c 0 [0, 0.0116]
c5dc_e 0 [0, 0.0102]
3mlda_e 0 [0, 0.00778]
5mta_e 0 [0, 0.00689]
sprm_c 0 [0, 0.00689]
sprm_e 0 [0, 0.00689]
4hphac_e 0 [0, 0.00667]
q10h2_e 0 [0, 0.00667]
ivcrn_e 0 [0, 0.00578]
bilglcur_e 0 [0, 0.00528]
co_e 0 [0, 0.00528]
pheme_e 0 [0, 0.00528]
pheacgln_e 0 [0, 0.00333]
model_CancerBiopsy3.summary(fva=True)IN FLUXES OUT FLUXES OBJECTIVES
----------------------------------------------- -------------------------------------------- -----------------------
id Flux Range id Flux Range biomass_reac... 0.0334
--------------- -------- -------------------- --------------- -------- -----------------
glc_D_e 0.329 [0.197, 1] h_e 0.716 [-0.411, 3.29]
o2_e 0.137 [-0.0058, 1] lac_L_e 0.578 [-0.09, 2.7]
gln_L_e 0.0462 [0.09, -0.153] cit_e 0.0521 [-0.012, 0.348]
lys_L_e 0.0198 [0.0198, 0.03] h2o_e 0.0312 [-0.371, 1.69]
val_L_e 0.019 [-0.000222, 0.03] ala_L_e 0.0291 [-0.0169, 0.294]
arg_L_e 0.012 [0.012, 0.012] co2_e 0.0288 [0, 1.73]
4mop_e 0.012 [0.00622, 0.012] ac_e 0.0281 [-0.012, 0.504]
crn_e 0.012 [0, 0.012] urate_e 0.0281 [0, 0.0847]
din_e 0.012 [0, 0.012] nh4_e 0.0245 [-0.012, 0.475]
o2s_e 0.012 [0, 0.012] uri_e 0.0197 [-0.012, 0.0634]
acac_e 0.012 [0.012, -0.012] pi_e 0.0133 [-0.04, 0.119]
3mob_e 0.012 [0.012, -0.0182] pyr_e 0.0122 [-0.012, 1.44]
gsn_e 0.012 [0.012, -0.0228] bhb_e 0.012 [0.012, -0.012]
dctp_n 0.012 [0.012, -0.0409] 3bcrn_e 0.00968 [0, 0.012]
cys_L_e 0.012 [0.012, -0.0464] dag_hs_e 0.00571 [-0.012, 0.183]
ppa_e 0.012 [0.012, -0.0625] Lcystin_c 0.00522 [0.00522, -0.024]
cytd_e 0.012 [0.012, -0.0634] glyc_e 0.00238 [-0.21, 0.299]
ps_hs_e 0.012 [0.012, -0.147] 3deccrn_e 0.00214 [0, 0.012]
pro_L_e 0.012 [0.012, -0.287] lac_D_e 0.001 [-0.001, 0.001]
ser_L_e 0.012 [0.012, -0.287] thymd_e 0.000891 [-0.012, 0.0994]
akg_e 0.012 [0.012, -0.331] 3ivcrn_e 0.000187 [0, 0.012]
thr_L_e 0.0104 [0.0104, 0.012] fe3_e 0 [-0.012, 0.545]
xylt_e 0.00969 [0.012, -0.328] oxa_e 0 [0, 0.452]
ile_L_e 0.00956 [0.00956, 0.012] vacc_e 0 [0, 0.452]
asn_L_e 0.00933 [0.00933, 0.012] elaid_e 0 [0, 0.449]
phe_L_e 0.00867 [0.00867, 0.012] no_e 0 [0, 0.429]
leu_L_e 0.00622 [0.00622, 0.012] gal_e 0 [0, 0.401]
chol_e 0.00552 [-0.0119, 0.012] ocdcea_e 0 [0, 0.349]
tyr_L_e 0.00533 [0.00533, 0.012] hdcea_e 0 [0, 0.328]
dgsn_e 0.00526 [0, 0.012] glyc_S_e 0 [0, 0.299]
met_L_e 0.00511 [0.00511, 0.012] acmana_e 0 [0, 0.294]
his_L_e 0.00422 [0.00422, 0.012] gly_e 0 [-0.03, 0.269]
arachd_e 0.00214 [0, 0.012] ha_pre1_e 0 [0, 0.193]
pe_hs_e 0.00208 [0.012, -0.147] nrvnc_e 0 [0, 0.175]
biomass_other_c 0.0018 [0.0018, 0.0018] ethamp_r 0 [0, 0.159]
adn_e 0.00179 [0.00868, -0.045] pe_hs_r 0 [-0.012, 0.147]
inost_e 0.000779 [0.000779, 0.000779] ha_e 0 [-0.012, 0.0898]
hdca_e 0.000584 [-0.0294, 0.3] clpnd_e 0 [0, 0.06]
sph1p_e 0.000584 [0.012, -0.147] dlnlcg_e 0 [0, 0.06]
pglyc_hs_e 0.000487 [0.000487, 0.000487] eicostet_e 0 [0, 0.06]
trp_L_e 0.000444 [0.000444, 0.012] lnlnca_e 0 [0, 0.06]
datp_n 0.00044 [0.00044, 0.00044] lnlncg_e 0 [0, 0.06]
dttp_n 0.000437 [0.000437, -0.0524] so4_e 0 [0, 0.0584]
dgtp_n 0.000331 [0.000331, 0.000331] taur_c 0 [0, 0.0584]
for_e 0.00021 [0.012, -0.0999] taur_e 0 [0, 0.0584]
fe2_e 0 [-0.012, 0.545] tchola_e 0 [0, 0.0546]
ocdca_e 0 [0, 0.07] chsterol_e 0 [0, 0.0524]
gthrd_e 0 [-0.0584, 0.06] 4mptnl_e 0 [0, 0.0511]
utp_e 0 [0, 0.02] aprgstrn_e 0 [0, 0.0511]
3hpvs_e 0 [0, 0.012] 5adtststerone_e 0 [0, 0.0495]
4hpro_LT_m 0 [0, 0.012] andrstrn_e 0 [0, 0.0495]
amp_e 0 [0, 0.012] fuc13galacgl... 0 [0, 0.048]
arab_L_e 0 [0, 0.012] fuc14galacgl... 0 [0, 0.048]
asp_L_e 0 [0, 0.012] gchola_e 0 [-0.012, 0.0465]
crvnc_e 0 [0, 0.012] galfucgalacg... 0 [0, 0.0456]
dad_2_e 0 [0, 0.012] 5adtststeron... 0 [0, 0.0441]
dcyt_e 0 [0, 0.012] andrstrnglc_e 0 [0, 0.0441]
dopa_e 0 [0, 0.012] tststeroneglc_e 0 [0, 0.044]
etoh_e 0 [0, 0.012] man_e 0 [-0.012, 0.036]
fmn_e 0 [0, 0.012] fuc_L_e 0 [0, 0.0347]
gam_e 0 [0, 0.012] 13_cis_retng... 0 [0, 0.024]
gluala_e 0 [0, 0.012] gthox_e 0 [0, 0.024]
leuktrA4_e 0 [0, 0.012] retnglc_e 0 [0, 0.024]
n2m2nmasn_e 0 [0, 0.012] fald_e 0 [-0.012, 0.024]
orn_e 0 [0, 0.012] meoh_e 0 [-0.012, 0.024]
ptrc_e 0 [0, 0.012] glyb_e 0 [0, 0.0238]
ptvstlac_e 0 [0, 0.012] 1mncam_e 0 [0, 0.0236]
retinol_e 0 [0, 0.012] Rtotal_e 0 [0, 0.0235]
spmd_e 0 [0, 0.012] lpchol_hs_e 0 [0, 0.0235]
2hb_e 0 [-0.00156, 0.012] pchol_hs_e 0 [0, 0.0235]
retn_e 0 [-0.012, 0.012] ppi_e 0 [0, 0.02]
ump_e 0 [0, 0.02]
fucfucfucgal... 0 [0, 0.016]
34dhoxpeg_e 0 [0, 0.012]
3ddcrn_e 0 [0, 0.012]
3hdececrn_e 0 [0, 0.012]
3hexdcrn_e 0 [0, 0.012]
3hpvstet_e 0 [0, 0.012]
3octdec2crn_e 0 [0, 0.012]
3octdeccrn_e 0 [0, 0.012]
3octdece1crn_e 0 [0, 0.012]
3tdcrn_e 0 [0, 0.012]
3tetd7ecoacrn_e 0 [0, 0.012]
3thexddcoacrn_e 0 [0, 0.012]
3ttetddcoacrn_e 0 [0, 0.012]
4abutn_e 0 [0, 0.012]
Asn_X_Ser_Thr_l 0 [0, 0.012]
CE1940_e 0 [0, 0.012]
abt_e 0 [0, 0.012]
ade_e 0 [0, 0.012]
adrn_e 0 [0, 0.012]
c6crn_e 0 [0, 0.012]
leuktrB4_e 0 [0, 0.012]
leuktrD4_e 0 [0, 0.012]
n5m2masn_g 0 [0, 0.012]
prpp_e 0 [0, 0.012]
ptvst_e 0 [0, 0.012]
ribflv_e 0 [0, 0.012]
HC01609_e 0 [-0.012, 0.012]
HC01610_e 0 [-0.012, 0.012]
anth_c 0 [0, 0.0116]
c5dc_e 0 [0, 0.0102]
3mlda_e 0 [0, 0.00778]
5mta_e 0 [0, 0.00689]
sprm_c 0 [0, 0.00689]
sprm_e 0 [0, 0.00689]
4hphac_e 0 [0, 0.00667]
q10h2_e 0 [0, 0.00667]
ivcrn_e 0 [0, 0.00578]
bilglcur_e 0 [0, 0.00528]
co_e 0 [0, 0.00528]
pheme_e 0 [0, 0.00528]
pheacgln_e 0 [0, 0.00333]
nac_e 0 [0.0116, -0.012]
lnlc_e 0 [0, -0.06]
model_CancerBiopsy4.summary(fva=True)IN FLUXES OUT FLUXES OBJECTIVES
----------------------------------------------- ------------------------------------------- -----------------------
id Flux Range id Flux Range biomass_reac... 0.0334
--------------- -------- -------------------- --------------- -------- ----------------
glc_D_e 0.352 [0.22, 1] h_e 0.7 [-0.357, 3.21]
o2_e 0.0656 [-0.0058, 1] lac_L_e 0.653 [-0.09, 2.68]
val_L_e 0.03 [-0.000222, 0.03] cys_L_e 0.0464 [-0.012, 0.0464]
Lcystin_c 0.024 [-0.00522, 0.024] pyr_e 0.0361 [-0.012, 1.33]
pi_e 0.0218 [0.04, -0.0836] co2_e 0.0315 [0, 1.71]
lys_L_e 0.0198 [0.0198, 0.03] h2o_e 0.0315 [-0.37, 1.68]
gly_e 0.018 [0.03, -0.269] ac_e 0.012 [-0.012, 0.477]
gln_L_e 0.0158 [0.09, -0.142] urate_e 0.012 [0, 0.0669]
arg_L_e 0.012 [0.012, 0.012] bhb_e 0.012 [0.012, -0.012]
leu_L_e 0.012 [0.00622, 0.012] glyc_S_e 0.0107 [0, 0.299]
din_e 0.012 [0, 0.012] leuktrD4_e 0.00979 [0, 0.012]
leuktrA4_e 0.012 [0, 0.012] dag_hs_e 0.00571 [-0.012, 0.183]
o2s_e 0.012 [0, 0.012] leuktrB4_e 0.00221 [0, 0.012]
acac_e 0.012 [-0.012, 0.012] nh4_e 0.00204 [-0.012, 0.451]
ps_hs_e 0.012 [0.012, -0.112] 3deccrn_e 0.00204 [0, 0.012]
pro_L_e 0.012 [0.012, -0.287] lac_D_e 0.001 [-0.001, 0.001]
ser_L_e 0.012 [0.012, -0.287] for_e 0.000681 [-0.012, 0.0871]
thr_L_e 0.0104 [0.0104, 0.012] fe3_e 0 [-0.012, 0.545]
gthrd_e 0.00979 [-0.0584, 0.06] elaid_e 0 [0, 0.449]
ile_L_e 0.00956 [0.00956, 0.012] oxa_e 0 [0, 0.446]
asn_L_e 0.00933 [0.00933, 0.012] no_e 0 [0, 0.406]
phe_L_e 0.00867 [0.00867, 0.012] gal_e 0 [0, 0.39]
4mop_e 0.00622 [0.00622, 0.012] ocdcea_e 0 [0, 0.34]
chol_e 0.00552 [-0.0116, 0.012] cit_e 0 [-0.012, 0.335]
tyr_L_e 0.00533 [0.00533, 0.012] hdcea_e 0 [0, 0.327]
met_L_e 0.00511 [0.00511, 0.012] xylt_e 0 [-0.012, 0.319]
his_L_e 0.00422 [0.00422, 0.012] glyc_e 0 [-0.21, 0.299]
pe_hs_e 0.00208 [0.012, -0.112] acmana_e 0 [0, 0.287]
arachd_e 0.00204 [0, 0.012] ha_pre1_e 0 [0, 0.185]
crn_e 0.00204 [0, 0.012] nrvnc_e 0 [0, 0.17]
gam_e 0.00182 [0, 0.012] ethamp_r 0 [0, 0.124]
biomass_other_c 0.0018 [0.0018, 0.0018] pe_hs_r 0 [-0.012, 0.112]
adn_e 0.00179 [0.00868, -0.021] ha_e 0 [-0.012, 0.086]
uri_e 0.00178 [0.012, -0.0517] thymd_e 0 [-0.012, 0.0757]
ala_L_e 0.00131 [0.0169, -0.294] ppa_e 0 [-0.012, 0.0616]
cytd_e 0.0013 [0.012, -0.0517] clpnd_e 0 [0, 0.06]
gsn_e 0.00121 [-0.0108, 0.012] dlnlcg_e 0 [0, 0.06]
inost_e 0.000779 [0.000779, 0.000779] eicostet_e 0 [0, 0.06]
hdca_e 0.000584 [-0.0291, 0.3] lnlnca_e 0 [0, 0.06]
sph1p_e 0.000584 [0.012, -0.112] lnlncg_e 0 [0, 0.06]
pglyc_hs_e 0.000487 [0.000487, 0.000487] so4_e 0 [0, 0.0584]
trp_L_e 0.000444 [0.000444, 0.012] taur_c 0 [0, 0.0584]
datp_n 0.00044 [0.00044, 0.00044] taur_e 0 [0, 0.0584]
dttp_n 0.000437 [0.000437, -0.0408] tchola_e 0 [0, 0.0535]
dgtp_n 0.000331 [0.000331, 0.000331] chsterol_e 0 [0, 0.0512]
dctp_n 0.000315 [0.000315, 0.000315] 4mptnl_e 0 [0, 0.0501]
fe2_e 0 [-0.012, 0.545] aprgstrn_e 0 [0, 0.0501]
ocdca_e 0 [0, 0.07] 5adtststerone_e 0 [0, 0.0486]
lnlc_e 0 [0, 0.06] andrstrn_e 0 [0, 0.0486]
utp_e 0 [0, 0.02] fuc13galacgl... 0 [0, 0.048]
3hpvs_e 0 [0, 0.012] fuc14galacgl... 0 [0, 0.048]
4hpro_LT_m 0 [0, 0.012] gchola_e 0 [-0.012, 0.0456]
amp_e 0 [0, 0.012] galfucgalacg... 0 [0, 0.0443]
arab_L_e 0 [0, 0.012] 5adtststeron... 0 [0, 0.0431]
asp_L_e 0 [0, 0.012] andrstrnglc_e 0 [0, 0.0431]
crvnc_e 0 [0, 0.012] tststeroneglc_e 0 [0, 0.0429]
dcyt_e 0 [0, 0.012] man_e 0 [-0.012, 0.036]
dopa_e 0 [0, 0.012] fuc_L_e 0 [0, 0.0338]
etoh_e 0 [0, 0.012] 13_cis_retng... 0 [0, 0.024]
fmn_e 0 [0, 0.012] gthox_e 0 [0, 0.024]
gluala_e 0 [0, 0.012] retnglc_e 0 [0, 0.024]
n2m2nmasn_e 0 [0, 0.012] 1mncam_e 0 [0, 0.0236]
orn_e 0 [0, 0.012] glyb_e 0 [0, 0.0234]
ptrc_e 0 [0, 0.012] Rtotal_e 0 [0, 0.0231]
ptvstlac_e 0 [0, 0.012] lpchol_hs_e 0 [0, 0.0231]
retinol_e 0 [0, 0.012] pchol_hs_e 0 [0, 0.0231]
spmd_e 0 [0, 0.012] ppi_e 0 [0, 0.02]
2hb_e 0 [-0.00156, 0.012] ump_e 0 [0, 0.02]
vacc_e 0 [0, -0.452] 3mob_e 0 [-0.012, 0.0182]
fucfucfucgal... 0 [0, 0.016]
34dhoxpeg_e 0 [0, 0.012]
3bcrn_e 0 [0, 0.012]
3ddcrn_e 0 [0, 0.012]
3hdececrn_e 0 [0, 0.012]
3hexdcrn_e 0 [0, 0.012]
3hpvstet_e 0 [0, 0.012]
3ivcrn_e 0 [0, 0.012]
3octdec2crn_e 0 [0, 0.012]
3octdeccrn_e 0 [0, 0.012]
3octdece1crn_e 0 [0, 0.012]
3tdcrn_e 0 [0, 0.012]
3tetd7ecoacrn_e 0 [0, 0.012]
3thexddcoacrn_e 0 [0, 0.012]
3ttetddcoacrn_e 0 [0, 0.012]
4abutn_e 0 [0, 0.012]
Asn_X_Ser_Thr_l 0 [0, 0.012]
CE1940_e 0 [0, 0.012]
abt_e 0 [0, 0.012]
ade_e 0 [0, 0.012]
adrn_e 0 [0, 0.012]
c6crn_e 0 [0, 0.012]
n5m2masn_g 0 [0, 0.012]
prpp_e 0 [0, 0.012]
ptvst_e 0 [0, 0.012]
ribflv_e 0 [0, 0.012]
HC01609_e 0 [-0.012, 0.012]
HC01610_e 0 [-0.012, 0.012]
fald_e 0 [-0.012, 0.012]
retn_e 0 [-0.012, 0.012]
anth_c 0 [0, 0.0116]
c5dc_e 0 [0, 0.0102]
3mlda_e 0 [0, 0.00778]
5mta_e 0 [0, 0.00689]
sprm_c 0 [0, 0.00689]
sprm_e 0 [0, 0.00689]
4hphac_e 0 [0, 0.00667]
q10h2_e 0 [0, 0.00667]
ivcrn_e 0 [0, 0.00578]
bilglcur_e 0 [0, 0.00528]
co_e 0 [0, 0.00528]
pheme_e 0 [0, 0.00528]
pheacgln_e 0 [0, 0.00333]
nac_e 0 [0.0116, -0.012]
model_CancerBiopsy5.summary(fva=True)IN FLUXES OUT FLUXES OBJECTIVES
----------------------------------------------- ------------------------------------------- -----------------------
id Flux Range id Flux Range biomass_reac... 0.0334
--------------- -------- -------------------- --------------- -------- ----------------
glc_D_e 0.365 [0.22, 1] h_e 0.725 [-0.0545, 3.21]
gln_L_e 0.09 [0.09, -0.13] lac_L_e 0.524 [-0.09, 2.68]
o2_e 0.0694 [-0.0058, 1] cit_e 0.0986 [-0.012, 0.339]
Lcystin_c 0.024 [-0.00522, 0.024] pyr_e 0.0872 [-0.012, 1.27]
pi_e 0.0218 [0.04, -0.0836] nh4_e 0.087 [-0.012, 0.427]
lys_L_e 0.0198 [0.0198, 0.03] ala_L_e 0.06 [-0.0169, 0.294]
gly_e 0.018 [0.03, -0.269] cys_L_e 0.0464 [-0.012, 0.0464]
gthrd_e 0.012 [-0.0584, 0.06] glyc_e 0.0315 [-0.21, 0.299]
arg_L_e 0.012 [0.012, 0.012] pro_L_e 0.012 [-0.012, 0.287]
asn_L_e 0.012 [0.00933, 0.012] leuktrD4_e 0.012 [0, 0.012]
leu_L_e 0.012 [0.00622, 0.012] ac_e 0.00983 [-0.012, 0.473]
asp_L_e 0.012 [0, 0.012] urate_e 0.00983 [0, 0.0721]
leuktrA4_e 0.012 [0, 0.012] HC01610_e 0.00788 [-0.012, 0.012]
o2s_e 0.012 [0, 0.012] dag_hs_e 0.00571 [-0.012, 0.183]
3mob_e 0.012 [0.012, -0.0182] 3bcrn_e 0.00312 [0, 0.012]
ppa_e 0.012 [0.012, -0.0617] 3deccrn_e 0.00204 [0, 0.012]
ps_hs_e 0.012 [0.012, -0.112] lac_D_e 0.001 [-0.001, 0.001]
ser_L_e 0.012 [0.012, -0.287] for_e 0.000681 [-0.012, 0.0992]
akg_e 0.012 [0.012, -0.324] co2_e 0 [0, 1.34]
val_L_e 0.0118 [-0.000222, 0.03] h2o_e 0 [-0.37, 1.33]
thr_L_e 0.0104 [0.0104, 0.012] fe3_e 0 [-0.012, 0.545]
din_e 0.00983 [0, 0.012] vacc_e 0 [0, 0.45]
ile_L_e 0.00956 [0.00956, 0.012] oxa_e 0 [0, 0.449]
phe_L_e 0.00867 [0.00867, 0.012] elaid_e 0 [0, 0.44]
gam_e 0.00794 [0, 0.012] no_e 0 [0, 0.401]
HC01609_e 0.00788 [0.012, -0.012] gal_e 0 [0, 0.39]
gluala_e 0.00717 [0, 0.012] hdcea_e 0 [0, 0.326]
4mop_e 0.00622 [0.00622, 0.012] ocdcea_e 0 [0, 0.314]
chol_e 0.00552 [-0.0116, 0.012] glyc_S_e 0 [0, 0.299]
tyr_L_e 0.00533 [0.00533, 0.012] acmana_e 0 [0, 0.287]
crn_e 0.00517 [0, 0.012] ha_pre1_e 0 [0, 0.184]
met_L_e 0.00511 [0.00511, 0.012] nrvnc_e 0 [0, 0.166]
his_L_e 0.00422 [0.00422, 0.012] ethamp_r 0 [0, 0.124]
pe_hs_e 0.00208 [0.012, -0.112] pe_hs_r 0 [-0.012, 0.112]
arachd_e 0.00204 [0, 0.012] ha_e 0 [-0.012, 0.0856]
biomass_other_c 0.0018 [0.0018, 0.0018] thymd_e 0 [-0.012, 0.0757]
adn_e 0.00179 [0.00868, -0.021] clpnd_e 0 [0, 0.06]
uri_e 0.00178 [0.012, -0.0517] dlnlcg_e 0 [0, 0.06]
cytd_e 0.0013 [0.012, -0.0517] lnlnca_e 0 [0, 0.06]
gsn_e 0.00121 [-0.0108, 0.012] lnlncg_e 0 [0, 0.06]
inost_e 0.000779 [0.000779, 0.000779] so4_e 0 [0, 0.0584]
hdca_e 0.000584 [-0.0291, 0.3] taur_c 0 [0, 0.0584]
sph1p_e 0.000584 [0.012, -0.112] taur_e 0 [0, 0.0584]
pglyc_hs_e 0.000487 [0.000487, 0.000487] tchola_e 0 [0, 0.0537]
trp_L_e 0.000444 [0.000444, 0.012] chsterol_e 0 [0, 0.0514]
datp_n 0.00044 [0.00044, 0.00044] 4mptnl_e 0 [0, 0.0501]
dttp_n 0.000437 [0.000437, -0.0408] aprgstrn_e 0 [0, 0.0501]
dgtp_n 0.000331 [0.000331, 0.000331] 5adtststerone_e 0 [0, 0.0487]
dctp_n 0.000315 [0.000315, 0.000315] andrstrn_e 0 [0, 0.0487]
ocdca_e 0 [0, 0.07] fuc13galacgl... 0 [0, 0.048]
utp_e 0 [0, 0.02] fuc14galacgl... 0 [0, 0.048]
3hpvs_e 0 [0, 0.012] gchola_e 0 [-0.012, 0.0457]
4hpro_LT_m 0 [0, 0.012] 5adtststeron... 0 [0, 0.0431]
amp_e 0 [0, 0.012] andrstrnglc_e 0 [0, 0.0431]
arab_L_e 0 [0, 0.012] tststeroneglc_e 0 [0, 0.043]
crvnc_e 0 [0, 0.012] galfucgalacg... 0 [0, 0.0424]
dcyt_e 0 [0, 0.012] man_e 0 [-0.012, 0.036]
dopa_e 0 [0, 0.012] fuc_L_e 0 [0, 0.0338]
etoh_e 0 [0, 0.012] 13_cis_retng... 0 [0, 0.024]
fmn_e 0 [0, 0.012] gthox_e 0 [0, 0.024]
n2m2nmasn_e 0 [0, 0.012] retnglc_e 0 [0, 0.024]
ptrc_e 0 [0, 0.012] fald_e 0 [-0.012, 0.024]
ptvstlac_e 0 [0, 0.012] meoh_e 0 [-0.012, 0.024]
retinol_e 0 [0, 0.012] 1mncam_e 0 [0, 0.0236]
spmd_e 0 [0, 0.012] glyb_e 0 [0, 0.0235]
2hb_e 0 [-0.00156, 0.012] Rtotal_e 0 [0, 0.0231]
nac_e 0 [-0.0116, 0.012] lpchol_hs_e 0 [0, 0.0231]
pheme_e 0 [0, -0.00528] pchol_hs_e 0 [0, 0.0231]
retn_e 0 [0.012, -0.012] ppi_e 0 [0, 0.02]
eicostet_e 0 [0, -0.06] udp_e 0 [0, 0.02]
xylt_e 0 [0.012, -0.319] ump_e 0 [0, 0.02]
fucfucfucgal... 0 [0, 0.016]
34dhoxpeg_e 0 [0, 0.012]
3ddcrn_e 0 [0, 0.012]
3hdececrn_e 0 [0, 0.012]
3hexdcrn_e 0 [0, 0.012]
3hpvstet_e 0 [0, 0.012]
3ivcrn_e 0 [0, 0.012]
3octdec2crn_e 0 [0, 0.012]
3octdeccrn_e 0 [0, 0.012]
3octdece1crn_e 0 [0, 0.012]
3tdcrn_e 0 [0, 0.012]
3tetd7ecoacrn_e 0 [0, 0.012]
3thexddcoacrn_e 0 [0, 0.012]
3ttetddcoacrn_e 0 [0, 0.012]
4abutn_e 0 [0, 0.012]
Asn_X_Ser_Thr_l 0 [0, 0.012]
CE1940_e 0 [0, 0.012]
abt_e 0 [0, 0.012]
ade_e 0 [0, 0.012]
adrn_e 0 [0, 0.012]
c6crn_e 0 [0, 0.012]
leuktrB4_e 0 [0, 0.012]
n5m2masn_g 0 [0, 0.012]
prpp_e 0 [0, 0.012]
ptvst_e 0 [0, 0.012]
ribflv_e 0 [0, 0.012]
acac_e 0 [-0.012, 0.012]
bhb_e 0 [-0.012, 0.012]
anth_c 0 [0, 0.0116]
c5dc_e 0 [0, 0.0102]
3mlda_e 0 [0, 0.00778]
5mta_e 0 [0, 0.00689]
sprm_c 0 [0, 0.00689]
sprm_e 0 [0, 0.00689]
4hphac_e 0 [0, 0.00667]
q10h2_e 0 [0, 0.00667]
ivcrn_e 0 [0, 0.00578]
bilglcur_e 0 [0, 0.00528]
co_e 0 [0, 0.00528]
pheacgln_e 0 [0, 0.00333]
lnlc_e 0 [0, -0.06]
fe2_e 0 [0.012, -0.545]
model_NormalBiopsy1.summary(fva=True)IN FLUXES OUT FLUXES OBJECTIVES
----------------------------------------------- ---------------------------------------------- ----------------------
id Flux Range id Flux Range biomass_reac... 0.022
--------------- -------- -------------------- --------------- -------- -------------------
o2_e 0.227 [0.193, 1] h_e 0.372 [-0.954, 3.14]
glc_D_e 0.116 [0.00605, 0.874] glyc_S_e 0.18 [0, 0.786]
lac_L_e 0.09 [-0.072, 0.09] ala_L_e 0.168 [-0.04, 0.359]
gthrd_e 0.0838 [-0.023, 0.09] mal_L_e 0.113 [-0.012, 0.289]
glyc_e 0.0427 [-0.012, 0.21] cgly_e 0.0802 [-0.012, 0.101]
atp_e 0.0407 [-0.0325, 0.8] ac_e 0.0667 [-0.012, 0.15]
lys_L_e 0.013 [0.013, 0.013] xmp_e 0.0388 [-0.000794, 0.832]
leu_L_e 0.012 [0.012, 0.012] pyr_e 0.0376 [-0.012, 0.15]
ps_hs_e 0.012 [0.00391, 0.012] oxa_e 0.012 [0, 0.488]
3mob_e 0.012 [0, 0.012] 3bcrn_e 0.012 [0, 0.012]
4hpro_LT_m 0.012 [0, 0.012] dctp_n 0.0118 [-0.012, 0.0538]
asp_L_e 0.012 [0, 0.012] utp_e 0.0108 [-0.02, 0.0458]
crn_e 0.012 [0, 0.012] pi_e 0.0108 [0, 1.76]
gam_e 0.012 [0, 0.012] ppi_e 0.0108 [0, 0.586]
glyc3p_e 0.012 [-0.0119, 0.012] dag_hs_e 0.00785 [-0.000385, 0.0235]
dcmp_e 0.012 [0.012, -0.0538] acac_e 0.00751 [0.00931, -0.012]
uri_e 0.012 [0.012, -0.0538] Rtotal_e 0.00363 [0, 0.217]
glu_L_e 0.012 [0.012, -0.101] h2o_e 0.00192 [1.73, -3]
akg_e 0.012 [0.012, -0.15] gthox_e 0.00179 [0, 0.0565]
ser_L_e 0.012 [0.012, -0.387] lac_D_e 0.001 [0, 0.001]
nh4_e 0.012 [0.012, -1.21] co2_e 0.000449 [0, 1.35]
gly_e 0.0119 [0.03, -0.312] for_e 0.000449 [-0.012, 0.04]
bhb_e 0.0102 [-0.00931, 0.012] amp_e 0 [-0.012, 0.833]
pro_L_e 0.00907 [0.00907, 0.00907] abt_e 0 [0, 0.552]
gln_L_e 0.00796 [0.09, -0.202] fe3_e 0 [-0.012, 0.545]
arg_L_e 0.0079 [0.0079, 0.0079] xylt_e 0 [-0.012, 0.54]
val_L_e 0.00776 [0.00776, 0.00776] hdcea_e 0 [0, 0.427]
thr_L_e 0.00688 [0.00688, 0.00688] man_e 0 [-0.012, 0.422]
ile_L_e 0.00629 [0.00629, 0.012] vacc_e 0 [0, 0.373]
asn_L_e 0.00615 [0.00615, 0.00615] ade_e 0 [0, 0.356]
phe_L_e 0.00571 [0.00571, 0.012] prpp_e 0 [0, 0.356]
lpchol_hs_e 0.00363 [0, 0.0119] aicar_e 0 [0, 0.342]
tyr_L_e 0.00351 [0.00351, 0.012] 5oxpro_e 0 [0, 0.309]
met_L_e 0.00337 [0.00337, 0.012] elaid_e 0 [0, 0.304]
his_L_e 0.00278 [0, 0.012] fum_e 0 [-0.012, 0.289]
pe_hs_e 0.00137 [0.012, -0.0189] ocdcea_e 0 [0, 0.219]
biomass_other_c 0.00119 [0.00119, 0.00119] gal_e 0 [0, 0.171]
cys_L_e 0.00102 [0.00102, 0.012] nrvnc_e 0 [0, 0.111]
cytd_e 0.000859 [0.012, -0.0538] dlnlcg_e 0 [0, 0.072]
inost_e 0.000513 [0.000513, 0.000513] lnlncg_e 0 [0, 0.072]
arachd_e 0.000449 [0, 0.012] pheme_e 0 [0, 0.0307]
hdca_e 0.000385 [-0.0116, 0.3] bilglcur_e 0 [0, 0.0291]
sph1p_e 0.000385 [0.000385, 0.012] co_e 0 [0, 0.0291]
pglyc_hs_e 0.000321 [0.000321, 0.012] bildglcur_e 0 [0, 0.0283]
trp_L_e 0.000293 [0.000293, 0.000293] fald_e 0 [-0.012, 0.024]
datp_n 0.00029 [0.012, -0.372] meoh_e 0 [-0.012, 0.024]
dttp_n 0.000288 [0.000288, -0.0117] pe_hs_r 0 [-0.012, 0.0189]
dgtp_n 0.000218 [0.000218, 0.000218] cholate_e 0 [0, 0.0156]
fe2_e 0 [-0.012, 0.545] 3mlda_e 0 [0, 0.0126]
lnlc_e 0 [-0.012, 0.06] 34dhoxpeg_e 0 [0, 0.012]
3hpvs_e 0 [0, 0.012] 3ddcrn_e 0 [0, 0.012]
4mop_e 0 [0, 0.012] 3deccrn_e 0 [0, 0.012]
arab_L_e 0 [0, 0.012] 3hdececrn_e 0 [0, 0.012]
carn_e 0 [0, 0.012] 3hexdcrn_e 0 [0, 0.012]
cit_e 0 [0, 0.012] 3hpvstet_e 0 [0, 0.012]
crvnc_e 0 [0, 0.012] 3ivcrn_e 0 [0, 0.012]
csa_e 0 [0, 0.012] 3octdec2crn_e 0 [0, 0.012]
dopa_e 0 [0, 0.012] 3octdeccrn_e 0 [0, 0.012]
etoh_e 0 [0, 0.012] 3octdece1crn_e 0 [0, 0.012]
fol_e 0 [0, 0.012] 3tdcrn_e 0 [0, 0.012]
gluala_e 0 [0, 0.012] 3tetd7ecoacrn_e 0 [0, 0.012]
ha_e 0 [0, 0.012] 3thexddcoacrn_e 0 [0, 0.012]
leuktrA4_e 0 [0, 0.012] 3ttetddcoacrn_e 0 [0, 0.012]
lnlnca_e 0 [0, 0.012] am19cs_e 0 [0, 0.012]
mag_hs_e 0 [0, 0.012] am1csa_e 0 [0, 0.012]
n2m2nmasn_e 0 [0, 0.012] am9csa_e 0 [0, 0.012]
o2s_e 0 [0, 0.012] c6crn_e 0 [0, 0.012]
octa_e 0 [0, 0.012] c8crn_e 0 [0, 0.012]
ptvstlac_e 0 [0, 0.012] eicostet_e 0 [0, 0.012]
thymd_e 0 [0, 0.012] fol_c 0 [0, 0.012]
gchola_e 0 [-0.00355, 0.012] ivcrn_e 0 [0, 0.012]
pnto_R_e 0 [0, 0.011] leuktrB4_e 0 [0, 0.012]
ahcys_e 0 [0, -0.00863] leuktrD4_e 0 [0, 0.012]
adrn_e 0 [0, -0.012] n5m2masn_g 0 [0, 0.012]
clpnd_e 0 [0, -0.024] ptvstm3_e 0 [0, 0.012]
HC01609_e 0 [-0.012, 0.012]
HC01610_e 0 [-0.012, 0.012]
1glyc_hs_e 0 [0, 0.0117]
ethamp_r 0 [0, 0.0116]
fuc14galacgl... 0 [0, 0.0116]
octdececoa_c 0 [0, 0.011]
so4_e 0 [0, 0.011]
taur_c 0 [0, 0.011]
taur_e 0 [0, 0.011]
4hphac_e 0 [0, 0.00849]
pchol_hs_e 0 [0, 0.00809]
pheacgln_e 0 [0, 0.00629]
HC00250_e 0 [0, 0.00549]
4mptnl_e 0 [0, 0.00355]
5adtststerone_e 0 [0, 0.00355]
andrstrn_e 0 [0, 0.00355]
andrstrnglc_e 0 [0, 0.00355]
aprgstrn_e 0 [0, 0.00355]
chsterol_e 0 [0, 0.00355]
ocdca_e 0 [0, -0.07]
model_NormalBiopsy2.summary(fva= True)IN FLUXES OUT FLUXES OBJECTIVES
----------------------------------------------- -------------------------------------------- ----------------------
id Flux Range id Flux Range biomass_reac... 0.022
--------------- -------- -------------------- --------------- -------- -----------------
glc_D_e 0.139 [0.00605, 1] h_e 0.34 [-0.872, 5.4]
o2_e 0.0726 [-0.0107, 1] lac_L_e 0.161 [-0.09, 2.81]
lys_L_e 0.013 [0.013, 0.013] pyr_e 0.15 [-0.012, 2.74]
leu_L_e 0.012 [0.012, 0.012] h2o_e 0.106 [3.23, -3.59]
gam_e 0.012 [0, 0.012] nh4_e 0.0205 [-0.012, 1.3]
o2s_e 0.012 [0, 0.012] cit_e 0.012 [-0.012, 0.385]
acac_e 0.012 [-0.00931, 0.012] ac_e 0.011 [0, 2.03]
akg_e 0.012 [0.012, -0.364] glyc_S_e 0.00715 [0, 1.33]
ser_L_e 0.012 [0.012, -0.387] bhb_e 0.00662 [0.00931, -0.012]
man_e 0.012 [0.012, -0.691] oxa_e 0.00645 [0, 0.62]
gly_e 0.0119 [0.03, -0.369] tmndnc_e 0.00539 [0, 0.024]
glu_L_e 0.0109 [0.012, -0.101] leuktrD4_e 0.00494 [0, 0.012]
pro_L_e 0.00907 [0.00907, 0.00907] 3bcrn_e 0.00491 [0, 0.012]
arg_L_e 0.0079 [0.0079, 0.0079] 5oxpro_e 0.00397 [0, 0.392]
val_L_e 0.00776 [0.00776, 0.00776] dcmp_e 0.00341 [-0.012, 0.0538]
crn_e 0.0076 [0, 0.012] Rtotal_e 0.00325 [0, 0.395]
gln_L_e 0.00717 [0.09, -0.282] abt_e 0.00284 [0, 0.774]
thr_L_e 0.00688 [0.00688, 0.00688] 3ivcrn_e 0.00269 [0, 0.012]
4hpro_LT_m 0.00645 [0, 0.012] lac_D_e 0.001 [0, 0.001]
ile_L_e 0.00629 [0.00629, 0.012] for_e 0.000449 [-0.012, 0.04]
asn_L_e 0.00615 [0.00615, 0.00615] co2_e 0 [0, 1.79]
phe_L_e 0.00571 [0.00571, 0.012] pi_e 0 [0, 1.76]
crvnc_e 0.00539 [0, 0.012] dgtp_m 0 [0, 0.856]
gthrd_e 0.00494 [-0.023, 0.09] datp_m 0 [0, 0.833]
leuktrA4_e 0.00494 [0, 0.012] amp_e 0 [-0.012, 0.833]
gluala_e 0.00397 [0, 0.012] xylt_e 0 [-0.012, 0.762]
ps_hs_e 0.00391 [0.00391, 0.012] aicar_e 0 [0, 0.614]
lpchol_hs_e 0.00363 [0, 0.0119] ppi_e 0 [0, 0.586]
dctp_n 0.00362 [0.012, -0.0538] fe3_e 0 [-0.012, 0.545]
tyr_L_e 0.00351 [0.00351, 0.012] elaid_e 0 [0, 0.428]
met_L_e 0.00337 [0.00337, 0.012] hdcea_e 0 [0, 0.428]
his_L_e 0.00278 [0, 0.012] ocdcea_e 0 [0, 0.428]
ha_e 0.00142 [0, 0.012] fum_e 0 [-0.012, 0.399]
pe_hs_e 0.00137 [0.012, -0.0189] mal_L_e 0 [-0.012, 0.399]
biomass_other_c 0.00119 [0.00119, 0.00119] gal_e 0 [0, 0.363]
atp_e 0.00118 [-0.0325, 0.8] ala_L_e 0 [-0.04, 0.359]
utp_e 0.00118 [0.02, -0.0458] ade_e 0 [0, 0.356]
cys_L_e 0.00102 [0.00102, 0.012] prpp_e 0 [0, 0.356]
cytd_e 0.000859 [0.012, -0.0538] nrvnc_e 0 [0, 0.272]
xmp_e 0.000794 [0.012, -0.832] cgly_e 0 [-0.012, 0.101]
inost_e 0.000513 [0.000513, 0.000513] dlnlcg_e 0 [0, 0.072]
asp_L_e 0.000413 [0, 0.012] lnlncg_e 0 [0, 0.072]
sph1p_e 0.000385 [0.000385, 0.012] gthox_e 0 [0, 0.0565]
pglyc_hs_e 0.000321 [0.000321, 0.012] uri_e 0 [-0.012, 0.0538]
trp_L_e 0.000293 [0.000293, 0.000293] pheme_e 0 [0, 0.038]
datp_n 0.00029 [0.012, -0.821] bilglcur_e 0 [0, 0.0366]
dttp_n 0.000288 [0.000288, -0.0117] co_e 0 [0, 0.0366]
dag_hs_e 0.000235 [0.000385, -0.0235] bildglcur_e 0 [0, 0.0359]
dgtp_n 0.000218 [0.012, -0.844] clpnd_e 0 [0, 0.024]
fe2_e 0 [-0.012, 0.545] fald_e 0 [-0.012, 0.024]
hdca_e 0 [-0.0116, 0.3] meoh_e 0 [-0.012, 0.024]
glyc_e 0 [-0.012, 0.21] pe_hs_r 0 [-0.012, 0.0189]
lnlc_e 0 [-0.012, 0.06] cholate_e 0 [0, 0.0156]
3mob_e 0 [0, 0.012] 3mlda_e 0 [0, 0.0126]
4mop_e 0 [0, 0.012] 34dhoxpeg_e 0 [0, 0.012]
arab_L_e 0 [0, 0.012] 3ddcrn_e 0 [0, 0.012]
arachd_e 0 [0, 0.012] 3deccrn_e 0 [0, 0.012]
carn_e 0 [0, 0.012] 3hdececrn_e 0 [0, 0.012]
csa_e 0 [0, 0.012] 3hexdcrn_e 0 [0, 0.012]
dopa_e 0 [0, 0.012] 3hpvstet_e 0 [0, 0.012]
etoh_e 0 [0, 0.012] 3octdec2crn_e 0 [0, 0.012]
fol_e 0 [0, 0.012] 3octdeccrn_e 0 [0, 0.012]
lnlnca_e 0 [0, 0.012] 3octdece1crn_e 0 [0, 0.012]
mag_hs_e 0 [0, 0.012] 3tdcrn_e 0 [0, 0.012]
n2m2nmasn_e 0 [0, 0.012] 3tetd7ecoacrn_e 0 [0, 0.012]
octa_e 0 [0, 0.012] 3thexddcoacrn_e 0 [0, 0.012]
ptvstlac_e 0 [0, 0.012] 3ttetddcoacrn_e 0 [0, 0.012]
retinol_e 0 [0, 0.012] adrn_e 0 [0, 0.012]
thymd_e 0 [0, 0.012] am19cs_e 0 [0, 0.012]
gchola_e 0 [-0.00355, 0.012] am1csa_e 0 [0, 0.012]
glyc3p_e 0 [-0.0119, 0.012] am9csa_e 0 [0, 0.012]
pnto_R_e 0 [0, 0.011] c6crn_e 0 [0, 0.012]
octdececoa_c 0 [0, -0.011] c8crn_e 0 [0, 0.012]
vacc_e 0 [0, -0.428] eicostet_e 0 [0, 0.012]
fol_c 0 [0, 0.012]
ivcrn_e 0 [0, 0.012]
leuktrB4_e 0 [0, 0.012]
n5m2masn_g 0 [0, 0.012]
ptvstm3_e 0 [0, 0.012]
retn_e 0 [0, 0.012]
HC01609_e 0 [-0.012, 0.012]
HC01610_e 0 [-0.012, 0.012]
1glyc_hs_e 0 [0, 0.0117]
ethamp_r 0 [0, 0.0116]
fuc14galacgl... 0 [0, 0.0116]
so4_e 0 [0, 0.011]
taur_c 0 [0, 0.011]
taur_e 0 [0, 0.011]
ahcys_e 0 [0, 0.00863]
4hphac_e 0 [0, 0.00849]
pchol_hs_e 0 [0, 0.00809]
pheacgln_e 0 [0, 0.00629]
HC00250_e 0 [0, 0.00549]
4mptnl_e 0 [0, 0.00355]
5adtststerone_e 0 [0, 0.00355]
andrstrn_e 0 [0, 0.00355]
andrstrnglc_e 0 [0, 0.00355]
aprgstrn_e 0 [0, 0.00355]
chsterol_e 0 [0, 0.00355]
3hpvs_e 0 [0, -0.012]
ocdca_e 0 [0, -0.07]
model_NormalBiopsy3.summary(fva=True)IN FLUXES OUT FLUXES OBJECTIVES
----------------------------------------------- ---------------------------------------------- ----------------------
id Flux Range id Flux Range biomass_reac... 0.022
--------------- -------- -------------------- --------------- -------- -------------------
glc_D_e 0.153 [0.00605, 1] h_e 0.379 [-0.977, 5.4]
o2_e 0.102 [-0.0149, 1] lac_L_e 0.272 [-0.09, 2.81]
lys_L_e 0.013 [0.013, 0.013] h2o_e 0.0766 [3.27, -3.59]
leu_L_e 0.012 [0.012, 0.012] pyr_e 0.0491 [-0.012, 2.75]
gam_e 0.012 [0, 0.012] cit_e 0.0475 [-0.012, 0.393]
o2s_e 0.012 [0, 0.012] nh4_e 0.0112 [-0.012, 1.3]
glyc3p_e 0.012 [-0.0119, 0.012] 3bcrn_e 0.0112 [0, 0.012]
glu_L_e 0.012 [0.012, -0.101] glyc_S_e 0.0111 [0, 1.33]
akg_e 0.012 [0.012, -0.371] dcmp_e 0.00915 [-0.012, 0.0538]
ser_L_e 0.012 [0.012, -0.387] cgly_e 0.00424 [-0.012, 0.101]
fum_e 0.012 [0.012, -0.407] dag_hs_e 0.00374 [-0.000385, 0.0235]
mal_L_e 0.012 [0.012, -0.407] Rtotal_e 0.00363 [0, 0.395]
gly_e 0.0119 [0.03, -0.369] tmndnc_e 0.00269 [0, 0.096]
3mob_e 0.0115 [0, 0.012] lac_D_e 0.001 [0, 0.001]
crn_e 0.0112 [0, 0.012] for_e 0.000449 [-0.012, 0.04]
cytd_e 0.01 [0.012, -0.0538] ac_e 0 [-0.012, 2.03]
pro_L_e 0.00907 [0.00907, 0.00907] co2_e 0 [0, 1.79]
arg_L_e 0.0079 [0.0079, 0.0079] pi_e 0 [0, 1.76]
ps_hs_e 0.00788 [0.00391, 0.012] dgtp_m 0 [0, 0.856]
val_L_e 0.00776 [0.00776, 0.00776] datp_m 0 [0, 0.833]
gln_L_e 0.00717 [0.09, -0.288] amp_e 0 [-0.012, 0.833]
thr_L_e 0.00688 [0.00688, 0.00688] abt_e 0 [0, 0.774]
ile_L_e 0.00629 [0.00629, 0.012] xylt_e 0 [-0.012, 0.762]
asn_L_e 0.00615 [0.00615, 0.00615] man_e 0 [-0.012, 0.691]
ocdca_e 0.00586 [0, 0.07] oxa_e 0 [0, 0.623]
phe_L_e 0.00571 [0.00571, 0.012] aicar_e 0 [0, 0.614]
gthrd_e 0.00424 [-0.023, 0.09] ppi_e 0 [0, 0.586]
lpchol_hs_e 0.00363 [0, 0.0119] fe3_e 0 [-0.012, 0.545]
tyr_L_e 0.00351 [0.00351, 0.012] elaid_e 0 [0, 0.428]
met_L_e 0.00337 [0.00337, 0.012] hdcea_e 0 [0, 0.428]
his_L_e 0.00278 [0, 0.012] ocdcea_e 0 [0, 0.428]
crvnc_e 0.00269 [0, 0.012] vacc_e 0 [0, 0.428]
acac_e 0.00269 [-0.00931, 0.012] 5oxpro_e 0 [0, 0.398]
pe_hs_e 0.00137 [0.012, -0.0189] gal_e 0 [0, 0.363]
biomass_other_c 0.00119 [0.00119, 0.00119] ala_L_e 0 [-0.04, 0.359]
atp_e 0.00118 [-0.0325, 0.8] ade_e 0 [0, 0.356]
utp_e 0.00118 [0.02, -0.0458] prpp_e 0 [0, 0.356]
cys_L_e 0.00102 [0.00102, 0.012] nrvnc_e 0 [0, 0.272]
xmp_e 0.000794 [0.012, -0.832] clpnd_e 0 [0, 0.096]
inost_e 0.000513 [0.000513, 0.000513] eicostet_e 0 [0, 0.084]
hdca_e 0.000385 [-0.0116, 0.3] dlnlcg_e 0 [0, 0.072]
sph1p_e 0.000385 [0.000385, 0.012] lnlncg_e 0 [0, 0.072]
pglyc_hs_e 0.000321 [0.000321, 0.012] lnlnca_e 0 [-0.012, 0.072]
trp_L_e 0.000293 [0.000293, 0.000293] gthox_e 0 [0, 0.0565]
datp_n 0.00029 [0.012, -0.821] uri_e 0 [-0.012, 0.0538]
dttp_n 0.000288 [0.000288, -0.0117] pheme_e 0 [0, 0.0429]
dgtp_n 0.000218 [0.012, -0.844] bilglcur_e 0 [0, 0.041]
dctp_n 0.000208 [0.012, -0.0538] co_e 0 [0, 0.041]
fe2_e 0 [-0.012, 0.545] bildglcur_e 0 [0, 0.04]
glyc_e 0 [-0.012, 0.21] fald_e 0 [-0.012, 0.024]
lnlc_e 0 [-0.012, 0.06] meoh_e 0 [-0.012, 0.024]
3hpvs_e 0 [0, 0.012] pe_hs_r 0 [-0.012, 0.0189]
4hpro_LT_m 0 [0, 0.012] cholate_e 0 [0, 0.0156]
4mop_e 0 [0, 0.012] 3mlda_e 0 [0, 0.0126]
arab_L_e 0 [0, 0.012] 34dhoxpeg_e 0 [0, 0.012]
arachd_e 0 [0, 0.012] 3ddcrn_e 0 [0, 0.012]
asp_L_e 0 [0, 0.012] 3deccrn_e 0 [0, 0.012]
carn_e 0 [0, 0.012] 3hdececrn_e 0 [0, 0.012]
csa_e 0 [0, 0.012] 3hexdcrn_e 0 [0, 0.012]
dopa_e 0 [0, 0.012] 3hpvstet_e 0 [0, 0.012]
etoh_e 0 [0, 0.012] 3ivcrn_e 0 [0, 0.012]
fol_e 0 [0, 0.012] 3octdec2crn_e 0 [0, 0.012]
gluala_e 0 [0, 0.012] 3octdeccrn_e 0 [0, 0.012]
ha_e 0 [0, 0.012] 3octdece1crn_e 0 [0, 0.012]
leuktrA4_e 0 [0, 0.012] 3tdcrn_e 0 [0, 0.012]
mag_hs_e 0 [0, 0.012] 3tetd7ecoacrn_e 0 [0, 0.012]
n2m2nmasn_e 0 [0, 0.012] 3thexddcoacrn_e 0 [0, 0.012]
octa_e 0 [0, 0.012] 3ttetddcoacrn_e 0 [0, 0.012]
ptvstlac_e 0 [0, 0.012] adrn_e 0 [0, 0.012]
retinol_e 0 [0, 0.012] am19cs_e 0 [0, 0.012]
thymd_e 0 [0, 0.012] am1csa_e 0 [0, 0.012]
gchola_e 0 [-0.00355, 0.012] am9csa_e 0 [0, 0.012]
ppa_e 0 [-0.00926, 0.012] c6crn_e 0 [0, 0.012]
bhb_e 0 [-0.00931, 0.012] c8crn_e 0 [0, 0.012]
pnto_R_e 0 [0, 0.011] fol_c 0 [0, 0.012]
octdececoa_c 0 [0, -0.011] ivcrn_e 0 [0, 0.012]
leuktrB4_e 0 [0, 0.012]
leuktrD4_e 0 [0, 0.012]
n5m2masn_g 0 [0, 0.012]
ptvstm3_e 0 [0, 0.012]
retn_e 0 [0, 0.012]
HC01609_e 0 [-0.012, 0.012]
HC01610_e 0 [-0.012, 0.012]
1glyc_hs_e 0 [0, 0.0117]
ethamp_r 0 [0, 0.0116]
fuc14galacgl... 0 [0, 0.0116]
so4_e 0 [0, 0.011]
taur_c 0 [0, 0.011]
taur_e 0 [0, 0.011]
ahcys_e 0 [0, 0.00863]
4hphac_e 0 [0, 0.00849]
pchol_hs_e 0 [0, 0.00809]
pheacgln_e 0 [0, 0.00629]
HC00250_e 0 [0, 0.00549]
4mptnl_e 0 [0, 0.00355]
5adtststerone_e 0 [0, 0.00355]
andrstrn_e 0 [0, 0.00355]
andrstrnglc_e 0 [0, 0.00355]
aprgstrn_e 0 [0, 0.00355]
chsterol_e 0 [0, 0.00355]
model_NormalBiopsy4.summary(fva=True)IN FLUXES OUT FLUXES OBJECTIVES
----------------------------------------------- ---------------------------------------------- ----------------------
id Flux Range id Flux Range biomass_reac... 0.022
--------------- -------- -------------------- --------------- -------- -------------------
o2_e 0.175 [0.16, 1] h_e 0.364 [-0.844, 3.47]
glc_D_e 0.123 [0.00605, 0.998] cit_e 0.135 [-0.012, 0.297]
gthrd_e 0.09 [-0.023, 0.09] glyc_S_e 0.114 [0, 0.866]
lac_L_e 0.0618 [-0.072, 0.09] ala_L_e 0.103 [-0.04, 0.359]
lys_L_e 0.013 [0.013, 0.013] cgly_e 0.09 [-0.012, 0.101]
gly_e 0.013 [0.03, -0.369] ac_e 0.0478 [-0.012, 0.15]
leu_L_e 0.012 [0.012, 0.012] h2o_e 0.0452 [1.69, -3.13]
ps_hs_e 0.012 [0.00391, 0.012] pyr_e 0.0283 [-0.012, 0.15]
asp_L_e 0.012 [0, 0.012] nh4_e 0.012 [-0.012, 1.3]
crn_e 0.012 [0, 0.012] 3bcrn_e 0.012 [0, 0.012]
gam_e 0.012 [0, 0.012] Rtotal_e 0.0116 [0, 0.243]
lpchol_hs_e 0.012 [0, 0.012] bhb_e 0.00931 [0.00931, -0.012]
o2s_e 0.012 [0, 0.012] dctp_m 0.00885 [0, 0.0658]
acac_e 0.012 [-0.00931, 0.012] glyb_e 0.00837 [0, 0.0124]
glyc3p_e 0.012 [0.012, -0.012] dag_hs_e 0.00785 [-0.000385, 0.0359]
glu_L_e 0.012 [0.012, -0.101] tmndnc_e 0.00269 [0, 0.096]
akg_e 0.012 [0.012, -0.15] lac_D_e 0.001 [0, 0.001]
fum_e 0.012 [0.012, -0.255] for_e 0.000449 [-0.012, 0.04]
mal_L_e 0.012 [0.012, -0.255] pheme_e 0.000142 [0, 0.032]
ser_L_e 0.012 [0.012, -0.387] pi_e 0 [0, 1.77]
pro_L_e 0.00907 [0.00907, 0.00907] co2_e 0 [0, 1.23]
dcmp_e 0.00906 [0.012, -0.0538] amp_e 0 [-0.012, 0.833]
gln_L_e 0.00796 [0.09, -0.192] abt_e 0 [0, 0.634]
arg_L_e 0.0079 [0.0079, 0.0079] xylt_e 0 [-0.012, 0.622]
val_L_e 0.00776 [0.00776, 0.00776] ppi_e 0 [0, 0.59]
thr_L_e 0.00688 [0.00688, 0.00688] fe3_e 0 [-0.012, 0.545]
ile_L_e 0.00629 [0.00629, 0.012] oxa_e 0 [0, 0.511]
asn_L_e 0.00615 [0.00615, 0.00615] man_e 0 [-0.012, 0.485]
phe_L_e 0.00571 [0.00571, 0.012] hdcea_e 0 [0, 0.429]
tyr_L_e 0.00351 [0.00351, 0.012] dgtp_m 0 [0, 0.42]
met_L_e 0.00337 [0.00337, 0.012] vacc_e 0 [0, 0.417]
his_L_e 0.00278 [0, 0.012] ade_e 0 [0, 0.359]
crvnc_e 0.00269 [0, 0.012] prpp_e 0 [0, 0.359]
pe_hs_e 0.00137 [0.012, -0.0189] elaid_e 0 [0, 0.346]
biomass_other_c 0.00119 [0.00119, 0.00119] aicar_e 0 [0, 0.345]
atp_e 0.00118 [-0.0325, 0.8] 5oxpro_e 0 [0, 0.299]
uri_e 0.00118 [0.012, -0.0538] ocdcea_e 0 [0, 0.26]
3mob_e 0.00114 [0, 0.012] gal_e 0 [0, 0.196]
cys_L_e 0.00102 [0.00102, 0.012] nrvnc_e 0 [0, 0.138]
cytd_e 0.000859 [0.012, -0.0538] clpnd_e 0 [0, 0.096]
xmp_e 0.000794 [0.012, -0.832] eicostet_e 0 [0, 0.084]
inost_e 0.000513 [0.000513, 0.000513] dlnlcg_e 0 [0, 0.072]
sph1p_e 0.000385 [0.000385, 0.012] lnlncg_e 0 [0, 0.072]
pglyc_hs_e 0.000321 [0.000321, 0.012] lnlnca_e 0 [-0.012, 0.072]
trp_L_e 0.000293 [0.000293, 0.000293] gthox_e 0 [0, 0.0565]
datp_n 0.00029 [0.012, -0.41] dctp_n 0 [-0.012, 0.0538]
dttp_n 0.000288 [0.000288, -0.0117] utp_e 0 [-0.02, 0.0458]
dgtp_n 0.000218 [0.012, -0.477] bilglcur_e 0 [0, 0.0309]
fe2_e 0.000142 [-0.012, 0.545] co_e 0 [0, 0.0309]
hdca_e 0 [-0.0116, 0.3] bildglcur_e 0 [0, 0.0305]
glyc_e 0 [-0.012, 0.21] fald_e 0 [-0.012, 0.024]
ocdca_e 0 [0, 0.07] meoh_e 0 [-0.012, 0.024]
lnlc_e 0 [-0.012, 0.06] pe_hs_r 0 [-0.012, 0.0189]
3hpvs_e 0 [0, 0.012] cholate_e 0 [0, 0.0156]
4hpro_LT_m 0 [0, 0.012] 3mlda_e 0 [0, 0.0126]
4mop_e 0 [0, 0.012] 34dhoxpeg_e 0 [0, 0.012]
arab_L_e 0 [0, 0.012] 3ddcrn_e 0 [0, 0.012]
arachd_e 0 [0, 0.012] 3deccrn_e 0 [0, 0.012]
carn_e 0 [0, 0.012] 3hdececrn_e 0 [0, 0.012]
csa_e 0 [0, 0.012] 3hexdcrn_e 0 [0, 0.012]
dopa_e 0 [0, 0.012] 3hpvstet_e 0 [0, 0.012]
etoh_e 0 [0, 0.012] 3ivcrn_e 0 [0, 0.012]
fol_e 0 [0, 0.012] 3octdec2crn_e 0 [0, 0.012]
gluala_e 0 [0, 0.012] 3octdeccrn_e 0 [0, 0.012]
ha_e 0 [0, 0.012] 3octdece1crn_e 0 [0, 0.012]
leuktrA4_e 0 [0, 0.012] 3tdcrn_e 0 [0, 0.012]
mag_hs_e 0 [0, 0.012] 3tetd7ecoacrn_e 0 [0, 0.012]
n2m2nmasn_e 0 [0, 0.012] 3thexddcoacrn_e 0 [0, 0.012]
octa_e 0 [0, 0.012] 3ttetddcoacrn_e 0 [0, 0.012]
ptvstlac_e 0 [0, 0.012] adrn_e 0 [0, 0.012]
retinol_e 0 [0, 0.012] am19cs_e 0 [0, 0.012]
thymd_e 0 [0, 0.012] am1csa_e 0 [0, 0.012]
gchola_e 0 [-0.00355, 0.012] am9csa_e 0 [0, 0.012]
pnto_R_e 0 [0, 0.011] c6crn_e 0 [0, 0.012]
ahcys_e 0 [0, -0.00863] c8crn_e 0 [0, 0.012]
fol_c 0 [0, 0.012]
ivcrn_e 0 [0, 0.012]
leuktrB4_e 0 [0, 0.012]
leuktrD4_e 0 [0, 0.012]
n5m2masn_g 0 [0, 0.012]
ptvstm3_e 0 [0, 0.012]
retn_e 0 [0, 0.012]
HC01609_e 0 [-0.012, 0.012]
HC01610_e 0 [-0.012, 0.012]
1glyc_hs_e 0 [0, 0.0117]
ethamp_r 0 [0, 0.0116]
fuc14galacgl... 0 [0, 0.0116]
octdececoa_c 0 [0, 0.011]
so4_e 0 [0, 0.011]
taur_c 0 [0, 0.011]
taur_e 0 [0, 0.011]
4hphac_e 0 [0, 0.00849]
pchol_hs_e 0 [0, 0.00809]
pheacgln_e 0 [0, 0.00629]
HC00250_e 0 [0, 0.00549]
4mptnl_e 0 [0, 0.00355]
5adtststerone_e 0 [0, 0.00355]
andrstrn_e 0 [0, 0.00355]
andrstrnglc_e 0 [0, 0.00355]
aprgstrn_e 0 [0, 0.00355]
chsterol_e 0 [0, 0.00355]
model_NormalBiopsy5.summary(fva=True)IN FLUXES OUT FLUXES OBJECTIVES
----------------------------------------------- ---------------------------------------------- ----------------------
id Flux Range id Flux Range biomass_reac... 0.022
--------------- -------- -------------------- --------------- -------- -------------------
glc_D_e 0.131 [0.00605, 1] h_e 0.317 [-0.977, 5.41]
o2_e 0.0844 [-0.0149, 1] lac_L_e 0.162 [-0.09, 2.81]
ala_L_e 0.0158 [0.04, -0.359] pyr_e 0.16 [-0.012, 2.75]
lys_L_e 0.013 [0.013, 0.013] h2o_e 0.148 [3.26, -3.59]
leu_L_e 0.012 [0.012, 0.012] bhb_e 0.00931 [0.00931, -0.012]
gam_e 0.012 [0, 0.012] cit_e 0.00748 [-0.012, 0.393]
o2s_e 0.012 [0, 0.012] leuktrD4_e 0.00397 [0, 0.012]
acac_e 0.012 [-0.00931, 0.012] Rtotal_e 0.00363 [0, 0.396]
glyc3p_e 0.012 [0.012, -0.012] dctp_m 0.00307 [0, 0.0658]
akg_e 0.012 [0.012, -0.371] tmndnc_e 0.00269 [0, 0.096]
man_e 0.012 [0.012, -0.691] dag_hs_e 0.000729 [-0.000385, 0.0359]
pro_L_e 0.00907 [0.00907, 0.00907] for_e 0.000449 [-0.012, 0.04]
arg_L_e 0.0079 [0.0079, 0.0079] co2_e 0 [0, 1.79]
val_L_e 0.00776 [0.00776, 0.00776] pi_e 0 [0, 1.77]
gly_e 0.0072 [0.03, -0.369] glyc_S_e 0 [0, 1.33]
gln_L_e 0.00717 [0.09, -0.288] dgtp_m 0 [0, 0.856]
thr_L_e 0.00688 [0.00688, 0.00688] amp_e 0 [-0.012, 0.833]
ile_L_e 0.00629 [0.00629, 0.012] abt_e 0 [0, 0.774]
asn_L_e 0.00615 [0.00615, 0.00615] xylt_e 0 [-0.012, 0.762]
phe_L_e 0.00571 [0.00571, 0.012] oxa_e 0 [0, 0.62]
ps_hs_e 0.00487 [0.00391, 0.012] aicar_e 0 [0, 0.614]
4hpro_LT_m 0.00465 [0, 0.012] ppi_e 0 [0, 0.59]
3mob_e 0.00434 [0, 0.012] fe3_e 0 [-0.012, 0.545]
gthrd_e 0.00397 [-0.023, 0.09] elaid_e 0 [0, 0.429]
leuktrA4_e 0.00397 [0, 0.012] hdcea_e 0 [0, 0.429]
lpchol_hs_e 0.00363 [0, 0.012] ocdcea_e 0 [0, 0.429]
tyr_L_e 0.00351 [0.00351, 0.012] vacc_e 0 [0, 0.429]
fum_e 0.00341 [0.012, -0.407] 5oxpro_e 0 [0, 0.398]
met_L_e 0.00337 [0.00337, 0.012] gal_e 0 [0, 0.363]
dcmp_e 0.00307 [0.012, -0.0538] ade_e 0 [0, 0.359]
glyc_e 0.00283 [-0.012, 0.21] prpp_e 0 [0, 0.359]
his_L_e 0.00278 [0, 0.012] nrvnc_e 0 [0, 0.272]
crvnc_e 0.00269 [0, 0.012] cgly_e 0 [-0.012, 0.101]
pe_hs_e 0.00137 [0.012, -0.0189] glu_L_e 0 [-0.012, 0.101]
biomass_other_c 0.00119 [0.00119, 0.00119] clpnd_e 0 [0, 0.096]
atp_e 0.00118 [-0.0325, 0.8] eicostet_e 0 [0, 0.084]
utp_e 0.00118 [0.02, -0.0458] dlnlcg_e 0 [0, 0.072]
cys_L_e 0.00102 [0.00102, 0.012] lnlncg_e 0 [0, 0.072]
cytd_e 0.000859 [0.012, -0.0538] lnlnca_e 0 [-0.012, 0.072]
xmp_e 0.000794 [0.012, -0.832] gthox_e 0 [0, 0.0565]
inost_e 0.000513 [0.000513, 0.000513] pheme_e 0 [0, 0.043]
hdca_e 0.000385 [-0.0116, 0.3] bilglcur_e 0 [0, 0.041]
sph1p_e 0.000385 [0.000385, 0.012] co_e 0 [0, 0.041]
pglyc_hs_e 0.000321 [0.000321, 0.012] bildglcur_e 0 [0, 0.0401]
ser_L_e 0.000301 [0.012, -0.387] fald_e 0 [-0.012, 0.024]
trp_L_e 0.000293 [0.000293, 0.000293] pe_hs_r 0 [-0.012, 0.0189]
datp_n 0.00029 [0.012, -0.821] cholate_e 0 [0, 0.0156]
dttp_n 0.000288 [0.000288, -0.0117] 3mlda_e 0 [0, 0.0126]
dgtp_n 0.000218 [0.012, -0.844] glyb_e 0 [0, 0.0124]
dctp_n 0.000208 [0.012, -0.0538] 34dhoxpeg_e 0 [0, 0.012]
fe2_e 0 [-0.012, 0.545] 3bcrn_e 0 [0, 0.012]
ocdca_e 0 [0, 0.07] 3ddcrn_e 0 [0, 0.012]
lnlc_e 0 [-0.012, 0.06] 3deccrn_e 0 [0, 0.012]
3hpvs_e 0 [0, 0.012] 3hdececrn_e 0 [0, 0.012]
4mop_e 0 [0, 0.012] 3hexdcrn_e 0 [0, 0.012]
arab_L_e 0 [0, 0.012] 3hpvstet_e 0 [0, 0.012]
asp_L_e 0 [0, 0.012] 3ivcrn_e 0 [0, 0.012]
carn_e 0 [0, 0.012] 3octdec2crn_e 0 [0, 0.012]
csa_e 0 [0, 0.012] 3octdeccrn_e 0 [0, 0.012]
etoh_e 0 [0, 0.012] 3octdece1crn_e 0 [0, 0.012]
fol_e 0 [0, 0.012] 3tdcrn_e 0 [0, 0.012]
gluala_e 0 [0, 0.012] 3tetd7ecoacrn_e 0 [0, 0.012]
ha_e 0 [0, 0.012] 3thexddcoacrn_e 0 [0, 0.012]
mag_hs_e 0 [0, 0.012] 3ttetddcoacrn_e 0 [0, 0.012]
n2m2nmasn_e 0 [0, 0.012] am19cs_e 0 [0, 0.012]
octa_e 0 [0, 0.012] am1csa_e 0 [0, 0.012]
ptvstlac_e 0 [0, 0.012] am9csa_e 0 [0, 0.012]
retinol_e 0 [0, 0.012] c6crn_e 0 [0, 0.012]
thymd_e 0 [0, 0.012] c8crn_e 0 [0, 0.012]
gchola_e 0 [-0.00355, 0.012] fol_c 0 [0, 0.012]
ppa_e 0 [-0.00926, 0.012] ivcrn_e 0 [0, 0.012]
pnto_R_e 0 [0, 0.011] leuktrB4_e 0 [0, 0.012]
octdececoa_c 0 [0, -0.011] n5m2masn_g 0 [0, 0.012]
adrn_e 0 [0, -0.012] ptvstm3_e 0 [0, 0.012]
meoh_e 0 [0.012, -0.024] retn_e 0 [0, 0.012]
uri_e 0 [0.012, -0.0538] HC01609_e 0 [-0.012, 0.012]
mal_L_e 0 [0.012, -0.407] HC01610_e 0 [-0.012, 0.012]
nh4_e 0 [0.012, -1.3] 1glyc_hs_e 0 [0, 0.0117]
ac_e 0 [0, -2.03] ethamp_r 0 [0, 0.0116]
fuc14galacgl... 0 [0, 0.0116]
so4_e 0 [0, 0.011]
taur_c 0 [0, 0.011]
taur_e 0 [0, 0.011]
ahcys_e 0 [0, 0.00863]
4hphac_e 0 [0, 0.00849]
pchol_hs_e 0 [0, 0.00809]
pheacgln_e 0 [0, 0.00629]
HC00250_e 0 [0, 0.00549]
4mptnl_e 0 [0, 0.00355]
5adtststerone_e 0 [0, 0.00355]
andrstrn_e 0 [0, 0.00355]
andrstrnglc_e 0 [0, 0.00355]
aprgstrn_e 0 [0, 0.00355]
chsterol_e 0 [0, 0.00355]
lac_D_e 0 [0, 0.001]
arachd_e 0 [0, -0.012]
crn_e 0 [0, -0.012]
dopa_e 0 [0, -0.012]
import pandas as pd
def get_drugable_targets(normal_Model, disease_Model, model_name, eps=0.01):
Nids = [r.id for r in normal_Model.reactions]
Dids = [r.id for r in disease_Model.reactions]
nmodel=normal_Model.copy()
dmodel=disease_Model.copy()
common_rxs = list(set(Nids) & set(Dids))
print("Common reactions size",len(common_rxs))
unique_Nrx = list(set(Nids) - set(Dids))
print("Normal unique reactions size",len(unique_Nrx))
unique_Drx = list(set(Dids) - set(Nids))
print("Disease unique reactions size",len(unique_Drx))
nflx0=normal_Model.optimize().f
dflx0=disease_Model.optimize().f
results={}
for rx in common_rxs:
#print(rx)
nbounds=nmodel.reactions.get_by_id(rx).bounds
dbounds=dmodel.reactions.get_by_id(rx).bounds
nmodel.reactions.get_by_id(rx).bounds=(-eps,eps)
dmodel.reactions.get_by_id(rx).bounds=(-eps,eps)
nfba=nmodel.optimize()
dfba=dmodel.optimize()
nflx1=nfba.f
dflx1=dfba.f
results[rx]={}
results[rx]["model"]=model_name
results[rx]["gene_rule"]=nmodel.reactions.get_by_id(rx).gene_reaction_rule
results[rx]["norm_flux"]=nflx0
results[rx]["dise_flux"]=dflx0
results[rx]["del_norm_flux"]=nflx1
results[rx]["del_dise_flux"]=dflx1
# results[rx]["norm_prolif_ratio"]=nflx1/nflx0
#results[rx]["dise_prolif_ratio"]=dflx1/dflx0
#results[rx]["norm_dise_ratio"]=(nflx1/nflx0)/(dflx1/dflx0)
nmodel.reactions.get_by_id(rx).bounds=nbounds
dmodel.reactions.get_by_id(rx).bounds=dbounds
for rx in unique_Nrx:
#print(rx)
nbounds=nmodel.reactions.get_by_id(rx).bounds
nmodel.reactions.get_by_id(rx).bounds=(-eps,eps)
nfba=nmodel.optimize()
nflx1=nfba.f
results[rx]={}
results[rx]["model"]=model_name
results[rx]["gene_rule"]=nmodel.reactions.get_by_id(rx).gene_reaction_rule
results[rx]["norm_flux"]=nflx0
results[rx]["dise_flux"]=dflx0
results[rx]["del_norm_flux"]=nflx1
results[rx]["del_dise_flux"]=dflx0
# results[rx]["norm_prolif_ratio"]=nflx1/nflx0
# results[rx]["dise_prolif_ratio"]=dflx0
# results[rx]["norm_dise_ratio"]=nflx1/nflx0
nmodel.reactions.get_by_id(rx).bounds=nbounds
for rx in unique_Drx:
#print(rx)
dbounds=dmodel.reactions.get_by_id(rx).bounds
dmodel.reactions.get_by_id(rx).bounds=(-eps,eps)
dfba=dmodel.optimize()
dflx1=dfba.f
results[rx]={}
results[rx]["model"]=model_name
results[rx]["gene_rule"]=dmodel.reactions.get_by_id(rx).gene_reaction_rule
results[rx]["norm_flux"]=nflx0
results[rx]["dise_flux"]=dflx0
results[rx]["del_norm_flux"]=nflx0
results[rx]["del_dise_flux"]=dflx1
#results[rx]["norm_prolif_ratio"]=nflx0
# results[rx]["dise_prolif_ratio"]=dflx1/dflx0
# results[rx]["norm_dise_ratio"]=1/(dflx1/dflx0)
dmodel.reactions.get_by_id(rx).bounds=dbounds
return(pd.DataFrame(results).transpose())
import random
import numpy
def shuffle(conf):
lst = [x for x in range(0,len(conf.items()))]
random.shuffle(lst)
return lst
def randomize_model(conf_scores):
lst=shuffle(conf_scores)
a=numpy.array(lst)
(rxindex,rxvalues) = zip(*conf_scores.items())
rxvalues=numpy.array(rxvalues)
nrxval=rxvalues[a]
dictionary = dict(zip(list(rxindex), list(nrxval)))
return(dictionary)from corda import CORDA
import string
import multiprocessing as mp
# define a randomized analysis function
def multiple_randomized_analysis(modelC, modelN, Recon, pos, metabolites, nrx=5, penaltyFac=1000):
f="ByopsiesPFbootstraping/Targets_pf_"+str(penaltyFac)+"_Biopsies_n_"+str(nrx)+"_"+str(pos)+".csv"
print(f)
cConf_scores=randomize_model(modelC)
nConf_scores=randomize_model(modelN)
cConf_scores["DM_4hrpo"]=3
cConf_scores["DM_datp_n_"]=3
cConf_scores["DM_dctp_n_"]=3
cConf_scores["DM_dgtp_n_"]=3
cConf_scores["DM_dttp_n_"]=3
cConf_scores["DM_Lcystin"]=3
cConf_scores["DM_pe_hs_LPAREN_r_RPAREN_"]=3
cConf_scores["EX_2hb_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_34hpp_"]=3
cConf_scores["EX_3hpvs_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_3mob_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_4mop_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_ac_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_acac_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_acald_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_acetone_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_acgam_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_acmana_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_ade_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_adn_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_adpcbl_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_akg_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_ala_B_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_ala_D_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_ala_L_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_am9csa_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_amp_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_arab_L_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_arachd_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_arg_L_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_asn_L_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_asp_L_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_atp_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_bhb_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_btn_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_ca2_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_carn_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_caro_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_cgly_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_chol_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_chsterol_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_cit_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_cl_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_CLPND_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_co2_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_creat_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_crn_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_crvnc_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_csa_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_csn_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_cys_L_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_cytd_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_dad_2_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_dag_hs_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_dcmp_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_dcyt_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_ddca_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_dgsn_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_dhdascb_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_din_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_dopa_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_drib_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_etoh_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_fald_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_fe2_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_fe2_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_fe3_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_fmn_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_fol_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_for_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_fru_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_fuc_L_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_fum_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_gal_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_gam_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_gchola_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_glc_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_glcur_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_gln_L_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_glu_L_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_gluala_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_gly_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_glyb_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_glyc_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_glyc3p_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_glygn2_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_gsn_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_gthox_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_gthrd_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_gua_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_h_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_h2o_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_ha_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_HC00250_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_HC01609_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_HC01610_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_hdca_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_hdcea_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_his_L_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_hxan_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_ile_L_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_inost_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_k_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_lac_L_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_lac_D_LPAREN_e_RPAREN_"]=-1
cConf_scores["EX_lcts_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_leu_L_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_leuktrA4_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_leuktrD4_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_leuktrE4_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_lnlc_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_lnlnca_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_lnlncg_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_lpchol_hs_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_lys_L_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_mag_hs_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_mal_L_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_malt_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_man_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_meoh_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_met_L_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_n2m2nmasn_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_na1_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_nac_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_ncam_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_nh4_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_no2_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_o2_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_o2s_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_ocdca_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_ocdcea_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_octa_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_orn_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_oxa_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_pe_hs_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_pglyc_hs_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_phe_L_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_pheme_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_pi_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_pnto_R_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_ppa_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_pro_L_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_prostgh2_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_ps_hs_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_ptrc_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_ptvstlac_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_pydam_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_pydx_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_pydx5p_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_pydxn_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_pyr_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_q10h2_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_retfa_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_retinol_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_retn_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_rib_D_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_ribflv_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_sbt_DASH_d_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_sel_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_ser_L_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_so4_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_sph1p_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_spmd_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_strch1_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_strch2_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_sucr_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_tag_hs_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_thm_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_thr_L_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_thymd_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_tre_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_trp_L_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_ttdca_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_tyr_L_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_ura_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_urea_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_uri_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_utp_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_val_L_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_xmp_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_xyl_D_LPAREN_e_RPAREN_"]=3
cConf_scores["EX_xylt_LPAREN_e_RPAREN_"]=3
cConf_scores["biomass_reaction"]=3
cConf_scores["biomass_DNA"]=3
cConf_scores["biomass_RNA"]=3
cConf_scores["biomass_carbohydrate"]=3
cConf_scores["biomass_lipid"]=3
cConf_scores["biomass_other"]=3
cConf_scores["biomass_protein"]=3
cConf_scores["DM_atp_c_"]=3
nConf_scores["DM_4hrpo"]=3
nConf_scores["DM_datp_n_"]=3
nConf_scores["DM_dctp_n_"]=3
nConf_scores["DM_dgtp_n_"]=3
nConf_scores["DM_dttp_n_"]=3
nConf_scores["DM_Lcystin"]=3
nConf_scores["DM_pe_hs_LPAREN_r_RPAREN_"]=3
nConf_scores["EX_2hb_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_34hpp_"]=3
nConf_scores["EX_3hpvs_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_3mob_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_4mop_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_ac_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_acac_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_acald_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_acetone_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_acgam_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_acmana_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_ade_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_adn_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_adpcbl_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_akg_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_ala_B_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_ala_D_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_ala_L_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_am9csa_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_amp_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_arab_L_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_arachd_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_arg_L_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_asn_L_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_asp_L_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_atp_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_bhb_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_btn_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_ca2_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_carn_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_caro_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_cgly_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_chol_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_chsterol_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_cit_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_cl_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_CLPND_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_co2_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_creat_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_crn_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_crvnc_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_csa_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_csn_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_cys_L_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_cytd_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_dad_2_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_dag_hs_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_dcmp_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_dcyt_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_ddca_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_dgsn_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_dhdascb_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_din_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_dopa_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_drib_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_etoh_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_fald_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_fe2_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_fe2_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_fe3_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_fmn_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_fol_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_for_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_fru_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_fuc_L_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_fum_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_gal_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_gam_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_gchola_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_glc_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_glcur_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_gln_L_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_glu_L_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_gluala_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_gly_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_glyb_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_glyc_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_glyc3p_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_glygn2_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_gsn_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_gthox_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_gthrd_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_gua_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_h_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_h2o_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_ha_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_HC00250_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_HC01609_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_HC01610_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_hdca_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_hdcea_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_his_L_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_hxan_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_ile_L_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_inost_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_k_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_lac_L_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_lac_D_LPAREN_e_RPAREN_"]=-1
nConf_scores["EX_lcts_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_leu_L_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_leuktrA4_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_leuktrD4_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_leuktrE4_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_lnlc_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_lnlnca_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_lnlncg_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_lpchol_hs_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_lys_L_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_mag_hs_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_mal_L_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_malt_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_man_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_meoh_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_met_L_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_n2m2nmasn_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_na1_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_nac_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_ncam_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_nh4_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_no2_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_o2_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_o2s_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_ocdca_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_ocdcea_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_octa_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_orn_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_oxa_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_pe_hs_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_pglyc_hs_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_phe_L_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_pheme_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_pi_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_pnto_R_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_ppa_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_pro_L_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_prostgh2_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_ps_hs_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_ptrc_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_ptvstlac_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_pydam_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_pydx_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_pydx5p_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_pydxn_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_pyr_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_q10h2_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_retfa_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_retinol_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_retn_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_rib_D_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_ribflv_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_sbt_DASH_d_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_sel_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_ser_L_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_so4_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_sph1p_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_spmd_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_strch1_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_strch2_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_sucr_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_tag_hs_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_thm_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_thr_L_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_thymd_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_tre_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_trp_L_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_ttdca_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_tyr_L_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_ura_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_urea_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_uri_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_utp_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_val_L_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_xmp_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_xyl_D_LPAREN_e_RPAREN_"]=3
nConf_scores["EX_xylt_LPAREN_e_RPAREN_"]=3
nConf_scores["biomass_reaction"]=3
nConf_scores["biomass_DNA"]=3
nConf_scores["biomass_RNA"]=3
nConf_scores["biomass_carbohydrate"]=3
nConf_scores["biomass_lipid"]=3
nConf_scores["biomass_other"]=3
nConf_scores["biomass_protein"]=3
nConf_scores["DM_atp_c_"]=3
opt_c= CORDA(model=Recon, confidence=cConf_scores, n=5, met_prod=metabolites, penalty_factor=1000 )
opt_n= CORDA(model=Recon, confidence=nConf_scores, n=5, met_prod=metabolites, penalty_factor=1000 )
opt_c.build()
opt_n.build()
model_c=opt_c.cobra_model(name="C")
model_n=opt_n.cobra_model(name="N")
cobra.io.write_sbml_model(model_c, "c_model_randomized_"+str(i)+".sbml")
cobra.io.write_sbml_model(model_n, "n_model_randomized_"+str(i)+".sbml")
targets=get_drugable_targets(model_n, model_c, "biopsys" )
targets.to_csv(f)
print("finished"+str(i))
output = mp.Queue(maxsize=12)
pool = mp.Pool(processes=12)
for i in range(656,1001):
pool.apply_async(multiple_randomized_analysis, args=(conf_CancerBiopsy,conf_NormalBiopsy,Recon2,i, metas))
pool.close()
pool.join()