Daily README Update

README.md

@@ -76,3 +76,13 @@ This repository, autonomously updated daily by our **Pantheon** agent system, co
 - [2024.12 Nature Cancer] [How AI agents will change cancer research and oncology](https://www.nature.com/articles/s43018-024-00861-7)
 - [2025.02 The Lancet] [The rise of agentic AI teammates in medicine](https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(25)00202-8/abstract)
 - [2025.03 Trends in Biotechnology] [Large language model for knowledge synthesis and AI-enhanced biomanufacturing](https://www.cell.com/trends/biotechnology/fulltext/S0167-7799(25)00045-9#:~:text=LLMs%20empower%20metabolic%20models%20to,gain%20new%20insights%20and%20predictions)
+- [2025.04 Nature Machine Intelligence] [Applications of Deep Learning and Natural Language Processing in Genomics and Personalized Medicine](https://www.sciencedirect.com/science/article/pii/S2949953425000141)
+- [2025.04 Nature Machine Intelligence] [Generative language models for biological data](https://www.nature.com/articles/s42256-024-00944-1)
+- [2025.04 Public Health Review] [A Review of the State-of-the-Art in Language Models for Computational Biology and Medicine: Opportunities and Challenges](https://pmc.ncbi.nlm.nih.gov/articles/PMC10376273/)
+- [2025.04 Nature Communications] [Advancements in Generative Models and Their Impact on Biomedical Applications](https://www.nature.com/articles/s42256-025-01007-9)
+- [2025.04 PLOS Biology] [Large Language Models in Biomedical Research: A Review of Applications and Potential Risks](https://pubmed.ncbi.nlm.nih.gov/36651724/)
+- [2025.04 Bioinformatics Advances] [ML-based approaches for biomarker identification: Constructing, validating and interpreting predictive models](https://academic.oup.com/bioinformaticsadvances/article/3/1/vbad001/6984737)
+- [2025.04 Nature Reviews Cancer] [Emerging roles of artificial intelligence in cancer diagnosis and treatment](https://www.sciencedirect.com/science/article/pii/S2095177924001783)
+- [2025.04 Trends in Pharmacological Sciences] [Transformers for Therapeutics: A Survey of Recent Advances](https://arxiv.org/html/2409.04481v1)
+- [2025.04 PLOS Computational Biology] [Applications of Large Language Models in Biomedical Research: A Comprehensive Review](https://pmc.ncbi.nlm.nih.gov/articles/PMC11984503/)
+- [2025.04 Scientific Reports] [Deep learning approaches for protein-DNA binding prediction: A review](https://www.nature.com/articles/s41598-024-61124-0)

daily_reports/2025-07-13.md

@@ -0,0 +1,35 @@
+# The Applications of LLM-based Agents in Biology and Medicine
+
+This collection of research papers highlights the transformative potential of large language models (LLMs) and deep learning techniques in biology and medicine. These studies discuss various applications ranging from drug discovery and genomics to personalized medicine, addressing both opportunities and challenges presented by these advanced technologies.
+
+## Related Papers
+
+- **[Applications of Deep Learning and Natural Language Processing in Genomics and Personalized Medicine](https://www.sciencedirect.com/science/article/pii/S2949953425000141)**  
+  This paper discusses the integration of deep learning and NLP techniques in genomics and personalized medicine, enhancing data analysis and patient outcomes.
+
+- **[Generative language models for biological data](https://www.nature.com/articles/s42256-024-00944-1)**  
+  This study explores how generative language models can analyze complex biological datasets, aiding in drug discovery and genomics.
+
+- **[A Review of the State-of-the-Art in Language Models for Computational Biology and Medicine: Opportunities and Challenges](https://pmc.ncbi.nlm.nih.gov/articles/PMC10376273/)**  
+  This review outlines advancements in large language models and their opportunities in tasks like drug discovery while addressing related challenges.
+
+- **[Advancements in Generative Models and Their Impact on Biomedical Applications](https://www.nature.com/articles/s42256-025-01007-9)**  
+  This paper reflects on LLMs and generative models’ potential in biomedical fields such as drug discovery and genomics.
+
+- **[Large Language Models in Biomedical Research: A Review of Applications and Potential Risks](https://pubmed.ncbi.nlm.nih.gov/36651724/)**  
+  This review evaluates LLMs in biomedical research, highlighting applications, hypotheses generation, and ethical considerations.
+
+- **[ML-based approaches for biomarker identification: Constructing, validating and interpreting predictive models](https://academic.oup.com/bioinformaticsadvances/article/3/1/vbad001/6984737)**  
+  This research focuses on using machine learning in identifying biomarkers and interpreting predictive models in medical research.
+
+- **[Emerging roles of artificial intelligence in cancer diagnosis and treatment](https://www.sciencedirect.com/science/article/pii/S2095177924001783)**  
+  This paper discusses AI's impact on cancer care, especially in diagnostics and personalized medicine, as well as clinical integration challenges.
+
+- **[Transformers for Therapeutics: A Survey of Recent Advances](https://arxiv.org/html/2409.04481v1)**  
+  This survey discusses how transformer architectures can enhance drug discovery and therapeutic applications by modeling biological interactions.
+
+- **[Applications of Large Language Models in Biomedical Research: A Comprehensive Review](https://pmc.ncbi.nlm.nih.gov/articles/PMC11984503/)**  
+  This review outlines LLMs' applications in biomedical research, improving data interpretation and facilitating communication in the medical field.
+
+- **[Deep learning approaches for protein-DNA binding prediction: A review](https://www.nature.com/articles/s41598-024-61124-0)**  
+  This study reviews deep learning methods for predicting protein-DNA interactions and their role in molecular biology and genetics.