Add GenoTEX and GenoMAS papers on gene expression analysis

[Liu-Hy]

Thank you for maintaining this excellent resource for the community. In this PR, we request to add two papers from our research lab that are relevant to the applications of LLM-based agents in biology and medicine:

1. GenoTEX (added to Benchmarks section): An LLM Agent Benchmark for Automated Gene Expression Data Analysis

   • Publication: MLCB 2025 Oral (2024.06)
   • arXiv: https://arxiv.org/abs/2406.15341
   • Code: https://github.com/Liu-Hy/GenoTEX
   • Website: https://liu-hy.github.io/GenoTEX/
   • GenoTEX provides a comprehensive benchmark dataset for evaluating automated methods for gene expression data analysis, with 1,384 analysis problems, expert-curated annotations, and standardized evaluation metrics.

2. GenoMAS (added to Agent papers section): A Multi-Agent Framework for Scientific Discovery via Code-Driven Gene Expression Analysis

   • Publication: Preprint under review (2025.07)
   • arXiv: https://arxiv.org/abs/2507.21035
   • Code: https://github.com/Liu-Hy/GenoMAS
   • Website: https://liu-hy.github.io/GenoMAS/
   • GenoMAS presents a team of six specialized LLM agents that orchestrate through typed message-passing protocols for automated gene expression analysis, achieving state-of-the-art performance on the GenoTEX benchmark.

Both papers focus on LLM-based agents for bioinformatics and genomic data analysis, which aligns well with the scope of this repository. The entries follow the existing formatting conventions with links to code repositories and project websites.

Thank you for considering our request.