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Published on: December 25, 2021
Toward interpretable foundation models for molecular biology
1Division of Human Genomics and Precision Medicine, Department of Medicine, University of California at San Diego, La Jolla, CA 92093, USA.
Abstract:
For machine learning models in molecular biology, explanation is as important as prediction. Encoding prior knowledge and treating interpretability as a first-class design objective accomplish both. We provide design elements and a checklist for the next generation of foundation models in molecular biology that are as interpretable as they are powerful.
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