AI RESEARCH
BIOGEN: Evidence-Grounded Multi-Agent Reasoning Framework for Transcriptomic Interpretation in Antimicrobial Resistance
arXiv CS.AI
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ArXi:2510.16082v3 Announce Type: replace-cross Interpreting gene clusters from RNA-seq remains challenging, especially in antimicrobial resistance studies where mechanistic context is essential for hypothesis generation. Conventional enrichment methods summarize co-expressed modules using predefined categories, but often return sparse results and lack cluster-specific, literature-linked explanations.