Enabling interpretable machine learning for biological data with reliability scores

• K. D. Ahlquist ,

  Roles Conceptualization, Formal analysis, Investigation, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

  * E-mail: kaileigh_ahlquist@alumni.brown.edu (KDA); sugdenl@duq.edu (LAS)

  Affiliations Center for Computational Molecular Biology, Brown University, Providence, Rhode Island, United States of America, Department of Molecular Biology, Cell Biology, and Biochemistry, Brown University, Providence, Rhode Island, United States of America

  https://orcid.org/0000-0001-6812-9458

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• Lauren A. Sugden ,

  Roles Conceptualization, Formal analysis, Investigation, Methodology, Software, Visualization, Writing – original draft, Writing – review & editing

  * E-mail: kaileigh_ahlquist@alumni.brown.edu (KDA); sugdenl@duq.edu (LAS)

  ¶‡ These authors are joint senior authors on this work.

  Affiliation Department of Mathematics and Computer Science, Duquesne University, Pittsburgh, Pennsylvania, United States of America

  https://orcid.org/0000-0003-3495-8359

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• Sohini Ramachandran

  Roles Conceptualization, Funding acquisition, Resources, Supervision, Writing – review & editing

  ¶‡ These authors are joint senior authors on this work.

  Affiliations Center for Computational Molecular Biology, Brown University, Providence, Rhode Island, United States of America, Department of Ecology, Evolution and Organismal Biology, Brown University, Providence, Rhode Island, United States of America, Data Science Initiative, Brown University, Providence, Rhode Island, United States of America

  https://orcid.org/0000-0002-9588-7964

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