A machine learning approach for predicting CRISPR-Cas9 cleavage efficiencies and patterns underlying its mechanism of action

• Shiran Abadi,

  Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

  Affiliation Department of Molecular Biology and Ecology of Plants, Tel Aviv University, Tel Aviv, Israel

  http://orcid.org/0000-0002-3932-6310

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• Winston X. Yan,

  Roles Data curation, Resources, Writing – review & editing

  Affiliations Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America, Graduate Program in Biophysics, Harvard Medical School, Boston, Massachusetts, United States of America, Harvard-MIT Division of Health Sciences and Technology, Harvard Medical School, Boston, Massachusetts, United States of America

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• David Amar,

  Roles Investigation, Software, Writing – review & editing

  Affiliations Blavatnik School of Computer Science, Tel-Aviv University, Tel Aviv, Israel, Division of Cardiovascular Medicine, Department of Medicine, Stanford University, Stanford, CA, United States of America

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• Itay Mayrose

  Roles Conceptualization, Funding acquisition, Investigation, Methodology, Project administration, Writing – original draft, Writing – review & editing

  * E-mail: itaymay@post.tau.ac.il

  Affiliation Department of Molecular Biology and Ecology of Plants, Tel Aviv University, Tel Aviv, Israel

  http://orcid.org/0000-0002-8460-1502

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