Large Language Model Agents for Biological Intelligence Across Genomics, Proteomics, Spatial Biology, and Biomedicine
Mar 1, 2026·,,,,,,,,·
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Sajib Acharjee Dip
Dipanwita Mallick
Uddip Acharjee Shuvo
Shovito Barua Soumma
Fazle Rafsani
Bikash Kumar Paul
Nazifa Ahmed Moumi
Shafayat Ahmed
Liqing Zhang
Abstract
Large language model (LLM) agents extend traditional LLMs by integrating reasoning, planning, tool use, and multimodal capabilities into autonomous workflows for biological research. This review examines how agentic AI is transforming genomics, proteomics, spatial biology, and biomedicine through automated hypothesis generation, experimental planning, data integration, and scientific discovery. The article discusses current applications, emerging frameworks, technical challenges, evaluation strategies, and future directions for deploying AI agents in biological and biomedical research. :contentReference[oaicite:1]{index=1}
Type
Publication
Briefings in Bioinformatics