Essential latent knowledge for protein-protein interactions: Analysis by an unsupervised learning approach

IEEE/ACM Transactions on Computational Biology and Bioinformatics

Volumn 2, Issue 2, 2005, Pages 119-130

  Mamitsuka, Hiroshi ^a  

^a KYOTO UNIVERSITY   (Japan)

Author keywords

Biology and genetics; Data mining; Machine learning; Mining methods and algorithms

Indexed keywords

ALGORITHMS; CELLS; GENETIC ENGINEERING; LEARNING SYSTEMS; MATHEMATICAL MODELS; MAXIMUM LIKELIHOOD ESTIMATION; PARAMETER ESTIMATION; PROBABILITY;

BIOLOGY AND GENETICS; CELLULAR PROCESSES; DATA SOURCES; MINING METHODS AND ALGORITHMS;

PROTEINS;

PROTEOME;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; CLUSTER ANALYSIS; EVALUATION; GENE EXPRESSION PROFILING; METABOLISM; METHODOLOGY; PHYSIOLOGY; PROTEIN ANALYSIS; SIGNAL TRANSDUCTION; VALIDATION STUDY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; GENE EXPRESSION PROFILING; PATTERN RECOGNITION, AUTOMATED; PROTEIN INTERACTION MAPPING; PROTEOME; SIGNAL TRANSDUCTION;

EID: 22944461117     PISSN: 15455963     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCBB.2005.23     Document Type: Article

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