Improved prediction of malaria degradomes by supervised learning with SVM and profile kernel

Genetica

Volumn 136, Issue 1, 2009, Pages 189-209

  Kuang, Rui ^a   Gu, Jianying ^b   Cai, Hong ^c   Wang, Yufeng ^a  

^a University of Minnesota   (United States)

^b CITY UNIVERSITY OF NEW YORK   (United States)

^c UNIVERSITY OF TEXAS AT SAN ANTONIO   (United States)

Author keywords

Malaria; Parasite; Plasmodium; Protease; SVM

Indexed keywords

PEPTIDE HYDROLASE; PROTOZOAL PROTEIN;

ANIMAL; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; CHEMISTRY; CLASSIFICATION; ENZYMOLOGY; METHODOLOGY; PHYLOGENY; PLASMODIUM; PROTEIN DATABASE; STATISTICAL MODEL;

ANIMALS; ARTIFICIAL INTELLIGENCE; DATABASES, PROTEIN; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; PEPTIDE HYDROLASES; PHYLOGENY; PLASMODIUM; PROTOZOAN PROTEINS;

PLASMODIUM PARASITES;

EID: 63949088197     PISSN: 00166707     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10709-008-9336-9     Document Type: Article

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