#35 · Tools & infrastructure
LLM agents and traceable toolkits are automating bioinformatics analysis workflows
The common thread is software architecture for automating and standardizing computational biology analyses. ToolsGenie 2.0 uses a ReAct-style multi-agent design with Docker-based tool selection to translate natural language queries into bioinformatics analyses. msmu, a Python package, addresses LC-MS proteomics post-search processing by organizing data in MuData objects with provenance logs that enable workflow replay. MCPmed, a community proposal, adapts the Model Context Protocol to expose bioinformatics web services, including GEO, STRING, and UCSC Cell Browser, to LLM agents. The dominant theme is LLM-driven orchestration layered over existing resources, with the proteomics toolkit contributing the traceability component. The items differ in maturity: two are preprints and one is a published proposal rather than an evaluated system, and no benchmark results appear in the item summaries.
Published papers
MCPmed: a call for Model Context Protocol-enabled bioinformatics web services for LLM-driven discovery.
Proposes MCPmed, a community effort adapting Model Context Protocol to bioinformatics web server backends (GEO, STRING, UCSC Cell Browser) so LLM agents can…
Preprints
ToolsGenie 2.0: A Scalable and Extensible Multi-Agent System for Bioinformatics Automation
ToolsGenie 2.0 is a multi-agent AI framework using ReAct architecture and Docker selection to automate bioinformatics analyses from natural language queries,…
msmu: a Python toolkit for modular and traceable LC-MS proteomics data analysis based on MuData
msmu is an open-source Python package for LC-MS proteomics post-search processing, using MuData objects with provenance logs enabling workflow replay and…
Topic history
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| #35 |