Bioinformatics & Computational Biology Specialist
Expert in designing and developing end-to-end computational pipelines for multi-omics data, advanced statistical analysis, and large-scale genomic research.
I am a bioinformatics engineer with hands-on experience in genomics, transcriptomics, metagenomics, machine learning, and statistical analysis.
I specialize in building reproducible, high-performance pipelines for large datasets, integrating multiple tools and programming languages.
My research and projects cover:
- Long-read and short-read sequencing (PacBio, ONT, Illumina, Sanger)
- RNA-Seq / IsoSeq analysis for differential gene expression, alternative splicing, and transcript discovery
- Variant calling (SNPs, indels, CNVs) and hybrid gene analysis
- Microbiome and metagenomic data processing
- Machine learning for genomics and transcriptomics (classification, regression, clustering)
- High-throughput computing and workflow optimization on HPC clusters
Programming & Scripting: Python, R, Bash, Shell, Perl
Bioinformatics & Omics Tools:
- Transcriptomics & Splicing: DEXSeq, DESeq2, LeafCutter, TAMA, StringTie2, Kallisto, Salmon, STAR, HISAT2, Ballgown
- Genomics & Variant Calling: Clair3, GATK, Minimap2, Sambamba, Sniffles2
- Metagenomics: Kraken2, MetaPhlAn, HUMAnN3, QIIME2
- Machine Learning & AI: scikit-learn, TensorFlow, PyTorch, XGBoost
Statistical & Visualization: R (ggplot2, PCA, clustering), Python (pandas, seaborn, matplotlib)
Other Tools & Platforms: Git/GitHub, Conda, Docker, Snakemake, HPC cluster computing
Repository: Equus_Fertility_SangerSeq
- Sanger sequencing of ACE and SPATA fertility genes in horses
- Variant calling, alignment, and quality control pipelines
- Goal: Identify SNPs/indels associated with fertility traits
Repository: Flycatcher-Project-M2
- PacBio IsoSeq transcriptome analysis in Ficedula flycatchers
- Differential splicing and gene expression analysis using DEXSeq, LeafCutter, DESeq2
- Characterization of splicing variants contributing to hybrid infertility
- Analyses across tissues, sexes, and species using HPC clusters
- Functional annotation of candidate splice variants
Repository: Patient-SMA-CHY-Farhat-Hached
- Targeted ONT sequencing of SMN1/SMN2 locus
- Variant calling with Clair3, CNV detection, and hybrid gene analysis
- Developed a masked reference approach to improve SMN1-specific variant detection
- Microbiome profiling with 16S/Shotgun metagenomics
- Taxonomic and functional analysis using Kraken2, MetaPhlAn, HUMAnN3
- Statistical analyses and visualization of community composition and diversity
- Supervised and unsupervised ML models for genomics and transcriptomics datasets
- Classification of disease-associated variants
- Gene expression clustering and dimensionality reduction (PCA, t-SNE, UMAP)
Repository: my-portfolio
- Interactive showcase of bioinformatics pipelines and project results
- Includes visualizations, workflows, and reproducible analyses
- Experienced in multi-omics data integration (genomics, transcriptomics, metagenomics)
- Skilled in long-read and short-read sequencing analysis
- Expert in machine learning applications in bioinformatics
- Proficient in HPC-based computation and reproducible workflow development
- Strong foundation in statistical genomics, transcriptomics, and hybrid analysis
- Collaborative experience with international research projects
- LinkedIn: www.linkedin.com/in/fadi-slimi
- Email: [email protected]
- GitHub: github.com/Fadis04