Aggregating residue-level protein language model embeddings with optimal transport.

ABSTRACT:

Motivation

Protein language models (PLMs) have emerged as powerful approaches for mapping protein sequences into embeddings suitable for various applications. As protein representation schemes, PLMs generate per-token (i.e. per-residue) representations, resulting in variable-sized outputs based on protein length. This variability poses a challenge for protein-level prediction tasks that require uniform-sized embeddings for consistent analysis across different proteins. Previous work has typically used average pooling to summarize token-level PLM outputs, but it is unclear whether this method effectively prioritizes the relevant information across token-level representations.

Results

We introduce a novel method utilizing optimal transport to convert variable-length PLM output

SUBMITTER: NaderiAlizadeh N 

PROVIDER: S-EPMC11961220 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature