Subcellular localization prediction through boosting association rules

IEEE/ACM Transactions on Computational Biology and Bioinformatics

Volumn 9, Issue 2, 2012, Pages 609-618

  Yoon, Yongwook ^a   Lee, Gary Geunbae ^a  

^a Pohang University of Science and Technology (POSTECH)   (South Korea)

Author keywords

bioinformatics (genome or protein) databases; Clustering classification and association rules; pattern recognition

Indexed keywords

AMINO ACID COMPOSITIONS; BENCHMARK DATA; BIOINFORMATICS (GENOME OR PROTEIN) DATABASE; BOOSTING ALGORITHM; C-TERMINUS; CLASSIFICATION PERFORMANCE; DOCUMENT CLASSIFICATION; N-TERMINALS; ONLINE PREDICTION; PROTEIN DATABASE; PROTEIN SEQUENCES; PROTEIN SUBCELLULAR LOCALIZATION; SORTING SIGNALS; SUBCELLULAR LOCALIZATIONS; SUBCELLULAR LOCATION; TEST COVERAGE; TEXT ANNOTATIONS;

AMINO ACIDS; ASSOCIATION RULES; BENCHMARKING; BIOINFORMATICS; CLASSIFICATION (OF INFORMATION); FEATURE EXTRACTION; FORECASTING; INFORMATION RETRIEVAL SYSTEMS; PATTERN RECOGNITION; SORTING;

PROTEINS;

PROTEIN; VEGETABLE PROTEIN;

ANIMAL; AUTOMATED PATTERN RECOGNITION; BIOLOGY; CHEMISTRY; CLASSIFICATION; CLUSTER ANALYSIS; INTRACELLULAR SPACE; PROCEDURES; PROTEIN DATABASE; SEQUENCE ANALYSIS; SUPPORT VECTOR MACHINE; ARTICLE; METHODOLOGY;

ANIMALS; CLUSTER ANALYSIS; COMPUTATIONAL BIOLOGY; DATABASES, PROTEIN; INTRACELLULAR SPACE; PATTERN RECOGNITION, AUTOMATED; PLANT PROTEINS; PROTEINS; SEQUENCE ANALYSIS, PROTEIN; SUPPORT VECTOR MACHINES;

EID: 84856466037     PISSN: 15455963     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCBB.2011.131     Document Type: Article

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