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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
Published on: July 25, 2013
Rethinking molecular evolution through protein language model embeddings
Rosa Fernández1, Sergi Valverde1, Aureliano Bombarely2
1Institute of Evolutionary Biology (CSIC-UPF), Barcelona, Spain.
Abstract:
Protein language models compress protein sequences into high-dimensional embeddings that capture biochemical, structural, and functional constraints without explicit supervision. We highlight that these embeddings encode rich evolutionary information, enabling new geometry-based views of homology, divergence, and convergence, and calling for a synthesis between classical molecular evolution and systematic evolutionary embedding analysis.
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