A comprehensive evaluation of large language models in mining gene relations and pathway knowledge.

ABSTRACT: Understanding complex biological pathways, including gene-gene interactions and gene regulatory networks, is critical for exploring disease mechanisms and drug development. Manual literature curation of biological pathways cannot keep up with the exponential growth of new discoveries in the literature. Large-scale language models (LLMs) trained on extensive text corpora contain rich biological information, and they can be mined as a biological knowledge graph. This study assesses 21 LLMs, including both application programming interface (API)-based models and open-source models in their capacities of retrieving biological knowledge. The evaluation focuses on predicting gene regulatory relations (activation, inhibition, and phosphorylation) and the Kyoto Encyclopedia of Genes and Genomes (K

SUBMITTER: Azam M 

PROVIDER: S-EPMC11446478 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature