Identification of protein functions using a machine-learning approach based on sequence-derived properties

Proteome Science

Volumn 7, Issue , 2009, Pages

  Lee, Bum Ju ^a   Shin, Moon Sun ^b   Oh, Young Joon ^a   Oh, Hae Seok ^c   Ryu, Keun Ho ^d  

^a Jungwon University   (South Korea)

^b Konkuk University   (South Korea)

^c Gachon University   (South Korea)

^d Chungbuk National University   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY; AMINO ACID SEQUENCE; ARTICLE; BIOINFORMATICS; BIOLOGICAL ACTIVITY; CELL COMPOSITION; COMPUTER PREDICTION; CONTROLLED STUDY; MATHEMATICAL COMPUTING; MOLECULAR MODEL; PROTEIN ANALYSIS; PROTEIN FUNCTION; RANDOM FOREST; SENSITIVITY AND SPECIFICITY; STRUCTURAL HOMOLOGY; SUPPORT VECTOR MACHINE;

EID: 69549097716     PISSN: None     EISSN: 14775956     Source Type: Journal    
DOI: 10.1186/1477-5956-7-27     Document Type: Article

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