Tyler M. Yasaka

An embedding-based framework enables statistical testing of gene-set function hypotheses inferred by large language models

An embedding-based statistical framework is developed that transforms gene and function descriptions into vector representations, enabling statistical testing of gene-gene and gene-function relationships and quantitative prioritization of de novo functional hypotheses inferred by LLMs.