Multi-kernel transfer learning based on Chou's PseAAC formulation for protein submitochondria localization

Journal of Theoretical Biology

Volumn 293, Issue , 2012, Pages 121-130

  Mei, Suyu ^a  

^a SHENYANG NORMAL UNIVERSITY   (China)

Author keywords

Gene ontology; Non parametric multiple kernel learning; Performance overestimation; Protein subcellular localization; Transfer learning

Indexed keywords

AMINO ACID; MITOCHONDRIAL PROTEIN;

DATA SET; HOMOLOGY; LEARNING; PERFORMANCE ASSESSMENT; PROTEIN;

AMINO ACID COMPOSITION; ARTICLE; CELLULAR DISTRIBUTION; CONTROLLED STUDY; MACHINE LEARNING; MULTI KERNEL TRANSFER LEARNING MODEL; NONPARAMETRIC TEST; PRIORITY JOURNAL; PROTEIN ANALYSIS; PROTEIN LOCALIZATION; PROTEIN SUBMITOCHONDRIA LOCALIZATION; PROTEIN TARGETING; SEQUENCE HOMOLOGY; STATISTICAL DISTRIBUTION; STATISTICAL MODEL;

ANIMALS; ARTIFICIAL INTELLIGENCE; COMPUTATIONAL BIOLOGY; DATABASES, PROTEIN; MITOCHONDRIAL MEMBRANES; MITOCHONDRIAL PROTEINS; MODELS, BIOLOGICAL; SUBMITOCHONDRIAL PARTICLES;

EID: 80155143429     PISSN: 00225193     EISSN: 10958541     Source Type: Journal    
DOI: 10.1016/j.jtbi.2011.10.015     Document Type: Article

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