A decomposition model to track gene expression signatures: preview on observer-independent classification of ovarian cancer

A number of algorithms and analytical models have been employed to reduce the multidimensional complexity of DNA array data and attempt to extract some meaningful interpretation of the results. These include clustering, principal components analysis, self-organizing maps, and support vector machine...

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Veröffentlicht in:	Bioinformatics (Oxford, England) England), 2002-12, Vol.18 (12), p.1617-1624
Hauptverfasser:	MARTOGLIO, Ann-Marie, MISKIN, James W, SMITH, Stephen K, MACKAY, David J. C
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Biological and medical sciences Cluster Analysis Cystadenoma - classification Cystadenoma - genetics Female Fundamental and applied biological sciences. Psychology Gene Expression - genetics Gene Expression Profiling - methods Gene Expression Regulation - genetics General aspects Humans Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects) Models, Genetic Models, Statistical Observer Variation Oligonucleotide Array Sequence Analysis - methods Ovarian Neoplasms - classification Ovarian Neoplasms - genetics Quality Control Reference Values Reproducibility of Results Sensitivity and Specificity Transcription, Genetic - genetics
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