A machine learning approach for predicting CRISPR-Cas9 cleavage efficiencies and patterns underlying its mechanism of action
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Title
A machine learning approach for predicting CRISPR-Cas9 cleavage efficiencies and patterns underlying its mechanism of action
Authors
Keywords
CRISPR, Enthalpy, Machine learning algorithms, Sequence motif analysis, Genome analysis, Machine learning, Sequence alignment, Forecasting
Journal
PLoS Computational Biology
Volume 13, Issue 10, Pages e1005807
Publisher
Public Library of Science (PLoS)
Online
2017-10-17
DOI
10.1371/journal.pcbi.1005807
References
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