Predicting the state of cysteines based on sequence information

Journal of Theoretical Biology

Volumn 267, Issue 3, 2010, Pages 312-318

  Guang, Xuanmin ^a   Guo, Yanzhi ^a   Xiao, Jiamin ^a   Wang, Xia ^a   Sun, Jing ^a   Xiong, Wenjia ^a   Li, Menglong ^a  

^a SICHUAN UNIVERSITY   (China)

Author keywords

Annotation information; Evolution information; F score function.; Support vector machine

Indexed keywords

CYSTEINE;

ACCURACY ASSESSMENT; ALGORITHM; AMINO ACID; PERFORMANCE ASSESSMENT; PREDICTION; PROTEIN; VECTOR;

ACCURACY; AMINO ACID COMPOSITION; AMINO ACID SEQUENCE; ARTICLE; CLASSIFICATION ALGORITHM; CONTROLLED STUDY; DATA ANALYSIS SOFTWARE; DISULFIDE BOND; EVOLUTIONARY ALGORITHM; PREDICTION; PRIORITY JOURNAL; PROCESS DEVELOPMENT; PROCESS OPTIMIZATION; PROTEIN SECONDARY STRUCTURE; SCORING SYSTEM; SENSITIVITY AND SPECIFICITY; SEQUENCE ANALYSIS; SEQUENCE DATABASE; SUPPORT VECTOR MACHINE;

ALGORITHMS; AMINO ACID SEQUENCE; AMINO ACIDS; ARTIFICIAL INTELLIGENCE; COMPUTATIONAL BIOLOGY; CYSTEINE; CYSTINE; DATABASES, PROTEIN; EVOLUTION, MOLECULAR; HYDROPHOBIC AND HYDROPHILIC INTERACTIONS; MOLECULAR SEQUENCE ANNOTATION; PROTEIN STRUCTURE, SECONDARY; PROTEINS; REPRODUCIBILITY OF RESULTS;

EID: 77956673246     PISSN: 00225193     EISSN: 10958541     Source Type: Journal    
DOI: 10.1016/j.jtbi.2010.09.002     Document Type: Article

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