aristoteleo · github-actions · Jul 20, 2025
diff --git a/README.md b/README.md
@@ -46,6 +46,7 @@ This repository, autonomously updated daily by our **Pantheon** agent system, co
 - [2025.03 Preprint] [IAN: An Intelligent System for Omics Data Analysis and Discovery](https://www.biorxiv.org/content/10.1101/2025.03.06.640921v1)
 - [2025.03 Preprint] [PharmAgents: Building a Virtual Pharma with Large Language Model Agents](https://arxiv.org/abs/2503.22164)
 - [2025.03 Preprint] [CompBioAgent: An LLM-powered agent for single-cell RNA-seq data exploration](https://www.biorxiv.org/content/10.1101/2025.03.17.643771v1)
+- [2025.03 Preprint] [Transforming the landscape of microbiome research with large language models](https://www.biorxiv.org/content/10.1101/2025.03.11.642548v1)
 
 ## Benchmarks
 
@@ -76,3 +77,11 @@ 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)
+- [2023.10 Nature Communications] [Abstract Biological Intelligence: Uncovering Molecular Embryology Using OpenAI's GPT-3](https://www.nature.com/articles/s42003-022-03036-1)
+
+## Addendum
+
+- **[Harnessing the Power of Language Models to Improve Health Equity Research](https://pmc.ncbi.nlm.nih.gov/articles/PMC11583719/)** (Journal of Health Equity, 2021)  
+  This paper discusses how language models can enhance health equity research by analyzing large datasets and providing insights into social determinants of health.  
+- **[Artificial intelligence-based solutions in healthcare: Applications, challenges, and future prospects](https://www.sciencedirect.com/science/article/pii/S2001037024003209)** (Health Informatics Journal, 2024)  
+  The paper examines the potential of LLMs in diagnostics and treatment planning in healthcare, addressing future challenges in AI deployment.
diff --git a/daily_reports/2025-07-20.md b/daily_reports/2025-07-20.md
@@ -0,0 +1,50 @@
+# The Applications of LLM-Based Agents in Biology and Medicine
+
+This collection of papers explores the transformative impact of Large Language Models (LLMs) across various domains of biology and medicine. The advancements in LLM technology have opened new avenues for research methodologies, clinical practices, drug discovery, and patient care. Here is a summary of recent research findings in this field:
+
+- **[Large Language Models for Drug Discovery: Modeling Molecules, Bioactivity, and Protein Structure](https://arxiv.org/abs/2503.00096)** (ArXiv, March 2025)  
+  This paper reviews the applications of LLMs in drug discovery, focusing on modeling chemical compounds, predicting bioactivity, and generating protein structures.
+
+- **[Leveraging Large Language Models for Biomedical Text Mining](https://www.sciencedirect.com/science/article/pii/S0092867424010705)** (Cell, 2024)  
+  This paper discusses the efficacy of LLMs in biomedical text mining, tasks like information extraction and literature summarization, and their potential to bridge knowledge gaps in healthcare.
+
+- **[Transforming the landscape of microbiome research with large language models](https://www.biorxiv.org/content/10.1101/2025.03.11.642548v1)** (bioRxiv, March 11, 2025)  
+  This paper shows how LLMs can enhance microbiome research through automation and supporting data interpretation.
+
+- **[Understanding the Applications of Artificial Intelligence in Biomedical Research](https://pmc.ncbi.nlm.nih.gov/articles/PMC12189880/)** (Journal of Biomedical Informatics, 2023)  
+  This article explores various applications of AI, including LLMs, in drug discovery and patient diagnosis, highlighting their impact on personalized medicine.
+
+- **[An Overview of Large Language Models in Biomedicine: Applications and Future Directions](https://link.springer.com/article/10.1007/s10462-024-10921-0)** (Artificial Intelligence, 2024)  
+  This comprehensive review focuses on LLMs in biomedicine, including their use in processing biological texts and assisting in clinical decision-making.
+
+- **[Leveraging Large Language Models for Drug Discovery and Biomedical Research](https://www.nature.com/articles/s43856-023-00370-1)** (Nature Reviews Drug Discovery, 2023)  
+  The paper discusses how LLMs can enhance biological and medical research, from data analysis to hypothesis generation.
+
+- **[Artificial Intelligence in Health Care: A Review](https://onlinelibrary.wiley.com/doi/full/10.1002/hcs2.61)** (Health Services Research, 2023)  
+  This review covers the applications of AI technologies, including language models, in improving clinical decision-making and patient care.
+
+- **[AML: A Generalized Architecture for Molecular Language Models](https://arxiv.org/abs/2310.05694)** (arXiv, October 2023)  
+  This paper introduces AML, a new architecture for molecular language models to enhance tasks in drug discovery and molecular biology.
+
+- **[Applications of Large Language Models in Biology and Medicine](https://link.springer.com/article/10.1007/s13721-024-00458-1)** (Biological Cybernetics, 2024)  
+  This paper discusses integrating LLMs into various biological and medical domains, improving methodologies and data analysis.
+
+- **[Leveraging large language models for the automated design of biomolecules](https://www.nature.com/articles/s41592-024-02354-y)** (Nature Methods, 2024)  
+  The article talks about using LLMs to automate biomolecule design, improving efficiency in biological research and therapeutic development.
+
+- **[Leveraging large language models for clinical decision-making: a systematic review](https://pubmed.ncbi.nlm.nih.gov/39554079/)** (Journal of Medical Internet Research, 2023)  
+  This systematic review explores LLM applications in clinical decision-making and their potential implications for patient care.
+
+- **[Abstract Biological Intelligence: Uncovering Molecular Embryology Using OpenAI's GPT-3](https://www.nature.com/articles/s42003-022-03036-1)** (Nature Communications, 2022)  
+  This study examines using GPT-3 in predicting molecular interactions during embryonic development and its implications for biological research.
+
+- **[Harnessing the Power of Language Models to Improve Health Equity Research](https://pmc.ncbi.nlm.nih.gov/articles/PMC11583719/)** (Journal of Health Equity, 2021)  
+  This paper discusses how language models can enhance health equity research by analyzing large datasets and providing insights into social determinants of health.
+
+- **[Efficient protein design with deep generative models](https://www.nature.com/articles/s41467-025-56989-2)** (Nature Communications, 2025)  
+  This paper presents an approach to protein design using deep generative models, which could advance applications in drug discovery.
+
+- **[Artificial intelligence-based solutions in healthcare: Applications, challenges, and future prospects](https://www.sciencedirect.com/science/article/pii/S2001037024003209)** (Health Informatics Journal, 2024)  
+  The paper examines the potential of LLMs in diagnostics and treatment planning in healthcare, addressing future challenges in AI deployment. 
+
+This body of work illustrates the significant role that LLMs can play in advancing biological and medical research, the integration of AI technologies, and the implications for healthcare practices.