ArticleBioinformatics advances2025
Enhancing gene set overrepresentation analysis with large language models.
Article in Bioinformatics advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed.
- GeneInsight: Condensing gene set knowledge via language models.PLoS computational biology · 2026Article
- An embedding-based framework enables statistical testing of gene-set function hypotheses inferred by large language models.Nature communications · 2026Article
- The microbial unknome, a repertoire for microbial chatting?Heredity · 2026Review
- AI-powered Immune Cell Knowledge Graph (ICKG) with granular immune contexts enables immune program interpretation.NPJ artificial intelligence · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Motivation: Gene set overrepresentation analysis (ORA) is widely used to interpret high-throughput transcriptomics and proteomics data, but traditional methods rely on human-curated gene set databases that lack flexibility. Results: We introduce Availability and implementation:
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.