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Title[redir]:
Metagenes and molecular pattern discovery using matrix factorization - PMC
Description:
We describe here the use of nonnegative matrix factorization (NMF), an algorithm based on decomposition by parts that can reduce the dimension of expression data from thousands of genes to a handful of metagenes. Coupled with a model selection ...
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Keywords {π}
nmf, data, samples, genes, clustering, matrix, expression, classes, consensus, fig, som, set, matrices, number, pnashtml, html, clusters, leukemia, selection, class, initial, cophenetic, google, scholar, doi, information, methods, coefficient, sample, cluster, aml, metagenes, model, gene, rank, correlation, allb, pubmed, pmc, decomposition, patterns, biological, conditions, robust, metagene, split, method, tumors, analysis, allt,
Topics {βοΈ}
pmc beta search divergence-based update equations norm-based update equations full structure inherent pnas web site supplementary materials included cancer-related microarray data childhood brain tumors [google scholar] 11 [google scholar] 12 sparse parts-based representation gene expression patterns cophenetic correlation Ο4 cophenetic correlation coefficients cophenetic correlation argues primitive nueroectodermal tumors distinct molecular patterns publisher site pdf cophenetic correlation coefficient predict patient outcome white line separates top branching point performance varied substantially intervals equally spaced greater algorithmic complexity cancer genomics program van de rijn highest cophenetic coefficient license information pmcid nmf update equations represent distinct tissues randomly initializing matrices random initial condition reordered consensus matrices highlights alternative decompositions incorrect assignments involve positive linear combination positive linear combinations acute myelogenous leukemia acute lymphoblastic leukemia gene expression pattern simultaneously monitor expression provide molecular portraits coupled divergence equations affymetrix hu6800 chips computational molecular biology traditional factorization methods molecular pattern discovery meaningful biological interpretation principal component analysis
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