A machine learning approach for the prediction of protein surface loop flexibility

Proteins: Structure, Function and Bioinformatics

Volumn 79, Issue 8, 2011, Pages 2467-2474

  Hwang, Howook ^a,b   Vreven, Thom ^a   Whitfield, Troy W ^a   Wiehe, Kevin ^b   Weng, Zhiping ^a,b  

^a UNIVERSITY OF MASSACHUSETTS MEDICAL SCHOOL   (United States)

^b BOSTON UNIVERSITY   (United States)

Author keywords

B factor; Backbone; Flexibility; Loop; Protein; Random Forest; SVM

Indexed keywords

PROTEIN CDC42; PROTEIN P67; RAC PROTEIN; RAN PROTEIN; RAS PROTEIN;

ACCURACY; ARTICLE; CONTROLLED STUDY; CRYSTALLOGRAPHY; MACHINE LEARNING; PREDICTION; PRIORITY JOURNAL; PROTEIN BINDING; PROTEIN CONFORMATION; PROTEIN STRUCTURE; RECEIVER OPERATING CHARACTERISTIC; SIGNAL TRANSDUCTION; SUPPORT VECTOR MACHINE; SURFACE PROPERTY;

ARTIFICIAL INTELLIGENCE; PROTEIN STRUCTURE, SECONDARY; PROTEINS;

EID: 79960075532     PISSN: 08873585     EISSN: 10970134     Source Type: Journal    
DOI: 10.1002/prot.23070     Document Type: Article

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