Text mining improves prediction of protein functional sites

PLoS ONE

Volumn 7, Issue 2, 2012, Pages

  Verspoor, Karin M ^a   Cohn, Judith D ^b   Ravikumar, Komandur E ^a   Wall, Michael E ^b,c  

^a UNIVERSITY OF COLORADO SCHOOL OF MEDICINE   (United States)

^b LOS ALAMOS NATIONAL LABORATORY   (United States)

^c CENTER FOR NONLINEAR STUDIES   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AMINO ACID SEQUENCE; ARTICLE; BINDING SITE; CATALYSIS; CONTROLLED STUDY; DATA MINING; GENE MAPPING; GENE MUTATION; PREDICTION; PROTEIN DETERMINATION; PROTEIN DOMAIN; PROTEIN FUNCTION; PROTEIN PROTEIN INTERACTION; SEQUENCE ALIGNMENT; SEQUENCE ANALYSIS; STRUCTURE ACTIVITY RELATION; STRUCTURE ANALYSIS; ANIMAL; BIOLOGY; CHEMICAL STRUCTURE; CHEMISTRY; COMPUTER PROGRAM; CONFORMATION; ENZYME ACTIVE SITE; HUMAN; METHODOLOGY; PROTEIN DATABASE; PROTEIN TERTIARY STRUCTURE; STATISTICAL MODEL; X RAY CRYSTALLOGRAPHY;

PROTEIN;

ANIMALS; BINDING SITES; CATALYTIC DOMAIN; COMPUTATIONAL BIOLOGY; CRYSTALLOGRAPHY, X-RAY; DATA MINING; DATABASES, PROTEIN; HUMANS; MODELS, MOLECULAR; MODELS, STATISTICAL; MOLECULAR CONFORMATION; PROTEIN STRUCTURE, TERTIARY; PROTEINS; SEQUENCE ANALYSIS, PROTEIN; SOFTWARE;

EID: 84857664634     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0032171     Document Type: Article

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