A trade-off between sample complexity and computational complexity in learning boolean networks from time-series data

IEEE/ACM Transactions on Computational Biology and Bioinformatics

Volumn 7, Issue 1, 2010, Pages 118-125

  Perkins, Theodore J ^a   Hallett, Michael T ^b  

^a OTTAWA HOSPITAL RESEARCH INSTITUTE   (Canada)

^b MCGILL UNIVERSITY   (Canada)

Author keywords

And association rules; Association rules.; Classification; Clustering; Feature extraction or construction; Machine learning; Parameter learning; Time series analysis

Indexed keywords

AND ASSOCIATION RULES; BOOLEAN NETWORKS; BOOLEAN VARIABLES; CLUSTERING FEATURE; COMPUTATIONAL PROBLEM; CONSTRUCTION MACHINES; CONTINUOUS TIME; EXPRESSION DATA; EXPRESSION LEVELS; INFERENCE PROBLEM; INPUT VARIABLES; KEY PROBLEMS; NETWORK INFERENCE; NUMBER OF SAMPLES; REGULATORY RELATIONSHIPS; SAMPLE COMPLEXITY; SIMPLIFIED MODELS; STRONG CORRELATION; TIME-SERIES DATA; TRACTABLE ALGORITHMS;

ASSOCIATION RULES; ASSOCIATIVE PROCESSING; BIOCHEMISTRY; CLUSTER ANALYSIS; COMPUTATIONAL COMPLEXITY; DESIGN OF EXPERIMENTS; FEATURE EXTRACTION; GENE EXPRESSION; HARMONIC ANALYSIS; LEARNING SYSTEMS; MOLECULAR BIOLOGY; TIME SERIES;

TIME SERIES ANALYSIS;

PROTEOME;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; BIOLOGICAL MODEL; COMPUTER SIMULATION; GENE EXPRESSION PROFILING; METABOLISM; METHODOLOGY; PHYSIOLOGY; SIGNAL PROCESSING; SIGNAL TRANSDUCTION; STATISTICAL MODEL; TIME;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; GENE EXPRESSION PROFILING; LOGISTIC MODELS; MODELS, BIOLOGICAL; PROTEOME; SIGNAL PROCESSING, COMPUTER-ASSISTED; SIGNAL TRANSDUCTION; TIME FACTORS;

EID: 76849097046     PISSN: 15455963     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCBB.2008.38     Document Type: Article

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