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GeneInsight: Condensing Gene Set Knowledge via Language Models

Chin, W. L.; Chen, K.; Lassmann, T.

2025-07-10 bioinformatics
10.1101/2025.07.07.663611 bioRxiv
Show abstract

Interpreting gene sets is often complicated by the overwhelming number of annotations associated with individual genes, making it difficult to extract meaningful biological insights. To address this issue, we developed GeneInsight, an AI-powered tool that combines advanced topic modelling with large language models to automatically synthesise diverse biological annotations from literature, gene ontologies, and databases such as STRING. GeneInsight consolidates extensive annotations into coherent thematic summaries that render such data readily interpretable, thereby enabling the rapid extraction of biologically significant insights that conventional enrichment analyses often overlook.

Published in PLOS Computational Biology (predicted rank #11) · training set

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The top 4 journals account for 50% of the predicted probability mass.

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20
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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.