AlphaFold 2: Why It Works and Its Implications for Understanding the Relationships of Protein Sequence, Structure, and Function
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Title
AlphaFold 2: Why It Works and Its Implications for Understanding the Relationships of Protein Sequence, Structure, and Function
Authors
Keywords
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Journal
Journal of Chemical Information and Modeling
Volume 61, Issue 10, Pages 4827-4831
Publisher
American Chemical Society (ACS)
Online
2021-09-30
DOI
10.1021/acs.jcim.1c01114
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- (2020) Tao Xie et al. SCIENCE
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- (2020) Jordan J. Clark et al. Scientific Reports
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