Bioinformatic approaches for predicting substrates of proteases

Journal of Bioinformatics and Computational Biology

Volumn 9, Issue 1, 2011, Pages 149-178

  Song, Jiangning ^a,b,c   Tan, Hao ^a   Boyd, Sarah E ^d   Shen, Hongbin ^e   Mahmood, Khalid ^a   Webb, Geoffrey I ^a   Akutsu, Tatsuya ^b   Whisstock, James C ^a   Pike, Robert N ^a  

^a MONASH UNIVERSITY   (Australia)

^b KYOTO UNIVERSITY   (Japan)

^c Chinese Academy of Sciences   (China)

^d LA TROBE UNIVERSITY   (Australia)

^e SHANGHAI JIAO TONG UNIVERSITY   (China)

Author keywords

bioinformatics; feature selection; machine learning; Proteases; sequence analysis; structural information; substrate cleavage site; substrate specificity; support vector machine

Indexed keywords

PEPTIDE HYDROLASE; PROTEIN; SOLVENT;

ALGORITHM; AMINO ACID SEQUENCE; ANIMAL; ARTIFICIAL INTELLIGENCE; BIOLOGY; CHEMISTRY; ENZYME ACTIVE SITE; ENZYME SPECIFICITY; EVALUATION; GENETICS; HUMAN; METABOLISM; MOLECULAR GENETICS; PROTEIN DATABASE; PROTEIN SECONDARY STRUCTURE; REVIEW;

ALGORITHMS; AMINO ACID SEQUENCE; ANIMALS; ARTIFICIAL INTELLIGENCE; CATALYTIC DOMAIN; COMPUTATIONAL BIOLOGY; DATABASES, PROTEIN; HUMANS; MOLECULAR SEQUENCE DATA; PEPTIDE HYDROLASES; PROTEIN STRUCTURE, SECONDARY; PROTEINS; SOLVENTS; SUBSTRATE SPECIFICITY;

EID: 79851510308     PISSN: 02197200     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0219720011005288     Document Type: Review

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