Sensitivity and specificity of inferring genetic regulatory interactions from microarray experiments with dynamic Bayesian networks

Motivation: Bayesian networks have been applied to infer genetic regulatory interactions from microarray gene expression data. This inference problem is particularly hard in that interactions between hundreds of genes have to be learned from very small data sets, typically containing only a few doze...

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Veröffentlicht in:	Bioinformatics 2003-11, Vol.19 (17), p.2271-2282
1. Verfasser:	HUSMEIER, Dirk
Format:	Artikel
Sprache:	eng
Schlagworte:	Bayes Theorem Biological and medical sciences Computer Simulation Fundamental and applied biological sciences. Psychology Gene Expression Profiling - methods Gene Expression Regulation - physiology General aspects Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects) Models, Genetic Models, Statistical Oligonucleotide Array Sequence Analysis - methods Reproducibility of Results Sensitivity and Specificity Signal Transduction - physiology Stochastic Processes
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