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Two sequence- and two structure-based ML models have learned different aspects of protein biochemistry.

Autor: Kulikova AV; Department of Integrative Biology, University of Texas at Austin, Austin, Texas, USA.; Center for Systems and Synthetic Biology, The Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX, USA., Diaz DJ; Department of Chemistry, The University of Texas at Austin, Austin, TX, USA.; Center for Systems and Synthetic Biology, The Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX, USA.; Institute for Foundations of Machine Learning (IFML), The University of Texas at Austin, Austin, TX, USA., Chen T; Institute for Foundations of Machine Learning (IFML), The University of Texas at Austin, Austin, TX, USA.; Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, USA., Jeffrey Cole T; Department of Integrative Biology, University of Texas at Austin, Austin, Texas, USA., Ellington AD; Center for Systems and Synthetic Biology, The Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX, USA., Wilke CO; Department of Integrative Biology, University of Texas at Austin, Austin, Texas, USA.

Publikováno v: BioRxiv : the preprint server for biology [bioRxiv] 2023 Jul 09. Date of Electronic Publication: 2023 Jul 09.