A novel model to predict O-glycosylation sites using a highly unbalanced dataset

Glycoconjugate Journal

Volumn 29, Issue 7, 2012, Pages 551-564

  Zhou, Kun ^a,b   Ai, Chunzhi ^a   Dong, Peipei ^c   Fan, Xuran ^a   Yang, Ling ^a  

^a DALIAN INSTITUTE OF CHEMICAL PHYSICS   (China)

^b UNIVERSITY OF CHINESE ACADEMY OF SCIENCES   (China)

^c DALIAN MEDICAL UNIVERSITY   (China)

Author keywords

Amino acid index; Feature selection; PP LDA; Protein glycosylation prediction

Indexed keywords

ACCURACY; AMINO TERMINAL SEQUENCE; ARTICLE; ARTIFICIAL NEURAL NETWORK; CARBOXY TERMINAL SEQUENCE; CONTROLLED STUDY; DISCRIMINANT ANALYSIS; GLYCOSYLATION; HYDROPHOBICITY; INTERMETHOD COMPARISON; MATHEMATICAL MODEL; PREDICTION; PRIORITY JOURNAL; PROBABILITY; SUPPORT VECTOR MACHINE; VALIDATION PROCESS;

DATABASES, PROTEIN; GLYCOPROTEINS; GLYCOSYLATION; MODELS, GENETIC; NEURAL NETWORKS (COMPUTER); PROTEIN STRUCTURE, TERTIARY; SEQUENCE ANALYSIS, PROTEIN; SOFTWARE;

EID: 84865796100     PISSN: 02820080     EISSN: 15734986     Source Type: Journal    
DOI: 10.1007/s10719-012-9434-x     Document Type: Article

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