Article

Benchmarking gene embeddings from sequence, expression, network, and text models for functional prediction tasks

2025-02-01

Abstract excerpt

Accurate, data-driven representations of genes are critical for interpreting high-throughput biological data, yet no consensus exists on the most effective embedding strategy for common functional prediction tasks. Here, we present a systematic comparison of 38 gene embedding methods derived from amino acid sequences, gene expression profiles, protein–protein interaction networks, and biomedical literature. We ben...

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Literature Corpus work: db5f9ec6-7ae9-57ce-9607-d277a3922a50
DOI: 10.1101/2025.01.29.635607

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