Genome-wide sequence-based prediction of peripheral proteins using a novel semi-supervised learning technique

BMC Bioinformatics

Volumn 11, Issue SUPPLL.1, 2010, Pages

  Bhardwaj, Nitin ^a,b   Gerstein, Mark ^b,c   Lu, Hui ^a  

^a University of Illinois at Chicago   (United States)

^b YALE UNIVERSITY   (United States)

^c Yale University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL PROCESS; MEMBRANE BINDING; MEMBRANE TRAFFICKING; PERIPHERAL PROTEINS; PRE-DEFINED CLASS; PROTEIN FUNCTION PREDICTION; SEMI-SUPERVISED LEARNING TECHNIQUES; TRADITIONAL APPROACHES;

BINDING ENERGY; FORECASTING; MEMBRANES; PROTEINS; BIOINFORMATICS; ITERATIVE METHODS;

SUPERVISED LEARNING;

PROTEIN;

ARTICLE; ARTIFICIAL INTELLIGENCE; CHEMICAL STRUCTURE; CHEMISTRY; GENOME; METHODOLOGY; PROTEIN CONFORMATION; PROTEOMICS; SEQUENCE ANALYSIS; SURFACE PROPERTY;

ARTIFICIAL INTELLIGENCE; GENOME; MODELS, MOLECULAR; PROTEIN CONFORMATION; PROTEINS; PROTEOMICS; SEQUENCE ANALYSIS, PROTEIN; SURFACE PROPERTIES;

EID: 75149114722     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-11-S1-S6     Document Type: Article

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