Sequence-based prediction of proteinprotein interactions using weighted sparse representation model combined with global encoding

BMC Bioinformatics

Volumn 17, Issue 1, 2016, Pages

  Huang, Yu An ^a   You, Zhu Hong ^b   Chen, Xing ^c   Chan, Keith ^d   Luo, Xin ^d  

^a SHENZHEN UNIVERSITY   (China)

^b CHINA UNIVERSITY OF MINING AND TECHNOLOGY   (China)

^c CHINESE ACADEMY OF SCIENCES   (China)

^d HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL METHODS; ENCODING (SYMBOLS); FORECASTING; MOLECULAR BIOLOGY; SUPPORT VECTOR MACHINES;

COMPUTATIONAL APPROACH; COMPUTATIONAL MODEL; EXPERIMENTAL METHODS; FALSE POSITIVE AND FALSE NEGATIVES; FEATURE REPRESENTATION; HIGH THROUGHPUT TECHNOLOGY; PROTEIN-PROTEIN INTERACTIONS; SPARSE REPRESENTATION;

PROTEINS;

AMINO ACID SEQUENCE; HELICOBACTER PYLORI; HUMAN; MODEL; NEIGHBORHOOD; NONHUMAN; PREDICTION; PROTEIN DOMAIN; PROTEOMICS; SPECIES; SUPPORT VECTOR MACHINE; BIOLOGY; CHEMISTRY; EVALUATION STUDY; METABOLISM; PROCEDURES; PROTEIN ANALYSIS; SEQUENCE ANALYSIS;

BACTERIAL PROTEIN; PROTEIN; SACCHAROMYCES CEREVISIAE PROTEIN;

BACTERIAL PROTEINS; COMPUTATIONAL BIOLOGY; HELICOBACTER PYLORI; HUMANS; PROTEIN INTERACTION MAPPING; PROTEINS; PROTEOMICS; SACCHAROMYCES CEREVISIAE PROTEINS; SEQUENCE ANALYSIS, PROTEIN; SUPPORT VECTOR MACHINE;

EID: 85007480726     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/s12859-016-1035-4     Document Type: Article

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