Predicting protein-protein interactions from sequence using correlation coefficient and high-quality interaction dataset

Amino Acids

Volumn 38, Issue 3, 2010, Pages 891-899

  Shi, Ming Guang ^a,b,c   Xia, Jun Feng ^a,b   Li, Xue Ling ^a   Huang, De Shuang ^a  

^a INSTITUTE OF INTELLIGENT MACHINES   (China)

^b UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA   (China)

^c HEFEI UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

Correlation coefficient; Gold standard negatives dataset; Gold standard positives dataset; Protein sequence; Protein protein interactions; Support vector machine

Indexed keywords

PROTEOME;

ARTICLE; CELL FUNCTION; CORRELATION COEFFICIENT; DATA MINING; GOLD STANDARD; INTERMETHOD COMPARISON; MATHEMATICAL ANALYSIS; NOISE; NONHUMAN; PREDICTION; PRIORITY JOURNAL; PROTEIN FUNCTION; PROTEIN PROTEIN INTERACTION; RESIDUE ANALYSIS; SACCHAROMYCES CEREVISIAE; SEQUENCE ANALYSIS; SUPPORT VECTOR MACHINE;

ALGORITHMS; AMINO ACID SEQUENCE; AMINO ACIDS; ARTIFICIAL INTELLIGENCE; BACTERIAL PROTEINS; COMPUTATIONAL BIOLOGY; DATA MINING; DATABASES, PROTEIN; HELICOBACTER PYLORI; MODELS, BIOLOGICAL; PROTEIN BINDING; PROTEIN INTERACTION MAPPING; PROTEOME; PROTEOMICS; SACCHAROMYCES CEREVISIAE PROTEINS;

SACCHAROMYCES CEREVISIAE;

EID: 77951667947     PISSN: 09394451     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00726-009-0295-y     Document Type: Article

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