LLMBDC: Language Model for Biological Domains Oriented Clustering of Gene Ontology
Gene Ontology (GO) enrichment analysis is a foundational tool for translating large-scale genomic data into biological insights, but typically yields hundreds of redundant terms that obscure overarching themes. Existing summarization tools rely on fixed similarity metrics (REVIGO, GOSemSim, clusterProfiler::simplify()), gene-overlap measures (Metascape), or static hierarchy mappings (GO-slim), and therefore cannot incorporate biological context. Manual curation provides context-aware grouping but is subjective and labor-intensive. A scalable, context-aware framework is needed to cluster GO terms into interpretable higher-order biological domains. Here we present LLMBDC (Large Language Mod...
| Authors | Ximing Ran, Jie Xu, Peng Jin et al. |
|---|---|
| Primary category | q-bio.GN |
| Published | 30 July 2026 |
| Last updated at source | 30 July 2026 |
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