Predicting plant protein subcellular multi-localization by Chou's PseAAC formulation based multi-label homolog knowledge transfer learning

Journal of Theoretical Biology

Volumn 310, Issue , 2012, Pages 80-87

  Mei, Suyu ^a  

^a SHENYANG NORMAL UNIVERSITY   (China)

Author keywords

Multi label learning; Nonparametric multiple kernel learning; Performance overestimation; Protein subcellular localization; Transfer learning

Indexed keywords

VEGETABLE PROTEIN;

EXPERIMENTAL STUDY; HOMOLOGY; MITOCHONDRION; NUMERICAL MODEL; PLANT; PROTEIN; TRANSFER FUNCTION;

AMINO ACID SEQUENCE; ARTICLE; CELLULAR DISTRIBUTION; KERNEL METHOD; MACHINE LEARNING; MATHEMATICAL COMPUTING; NONHUMAN; PREDICTION; PRIORITY JOURNAL; PROBABILITY; PROTEIN DATABASE; PROTEIN EXPRESSION; PROTEIN LOCALIZATION; PROTEIN TARGETING; QUALITY CONTROL; SEQUENCE HOMOLOGY; VALIDATION PROCESS;

ARTIFICIAL INTELLIGENCE; COMPUTATIONAL BIOLOGY; DATABASES, PROTEIN; PLANT PROTEINS; PROTEIN TRANSPORT; SEQUENCE HOMOLOGY, AMINO ACID; SOFTWARE; SUBCELLULAR FRACTIONS;

EID: 84863695726     PISSN: 00225193     EISSN: 10958541     Source Type: Journal    
DOI: 10.1016/j.jtbi.2012.06.028     Document Type: Article

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