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Arxiv
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PLM-eXplain: Divide and Conquer the Protein Embedding Space
- Protein language models (PLMs) have been successful in generating powerful sequence representations for computational biology.
- A new approach called PLM-eXplain (PLM-X) is introduced, which makes PLMs more interpretable and facilitates actionable insights.
- PLM-X factors PLM embeddings into two components: an interpretable subspace based on established biochemical features and a residual subspace preserving predictive power.
- The effectiveness of PLM-X is demonstrated through protein-level classification tasks, maintaining high performance while enabling biological interpretation.
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