bioNMF: a versatile tool for non-negative matrix factorization in biology

Pascual-Montano, Alberto; Carmona-Sáez, Pedro; Chagoyen, Mónica; Tirado, Francisco; Carazo, José Marı́a; Pascual-Marqui, Roberto D.

doi:10.1186/1471-2105-7-366

Cited by 79 publications

(68 citation statements)

References 26 publications

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“…These genes were subsequently validated using RT-PCR. The analytical tools available in the R/BioConductor package (http://www.r-project.org, http://www.bioconductor.org), bioNMF (20) and TMev (http://www.tm4.org) were utilized in these computations.…”

Section: Methodsmentioning

confidence: 99%

Altered Gene Expression in Morphologically Normal Epithelial Cells from Heterozygous Carriers of BRCA1 or BRCA2 Mutations

Bellacosa

Godwin

Peri

et al. 2010

Cancer Prevention Research

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We hypothesized that cells bearing a single inherited "hit" in a tumor suppressor gene express an altered mRNA repertoire that may identify targets for measures that could delay or even prevent progression to carcinoma. We report here on the transcriptomes of primary breast and ovarian epithelial cells cultured from BRCA1 and BRCA2 mutation carriers and controls. Our comparison analyses identified multiple changes in gene expression, in both tissues for both mutations, which were validated independently by real-time reverse transcription-PCR analysis. Several of the differentially expressed genes had been previously proposed as cancer markers, including mammaglobin in breast cancer and serum amyloid in ovarian cancer. These findings show that heterozygosity for a mutant tumor suppressor gene can alter the expression profiles of phenotypically normal epithelial cells in a genespecific manner; these detectable effects of "one hit" represent early molecular changes in tumorigenesis that may serve as novel biomarkers of cancer risk and as targets for chemoprevention. Cancer Prev Res; 3(1); 48-61. ©2010 AACR.

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Section: Methodsmentioning

confidence: 99%

Altered Gene Expression in Morphologically Normal Epithelial Cells from Heterozygous Carriers of BRCA1 or BRCA2 Mutations

Bellacosa

Godwin

Peri

et al. 2010

Cancer Prevention Research

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“…In 2006, we introduce one of such standalone applications, bioNMF (12), which implements the NMF methodology in different analysis contexts to support some of the most popular applications of this new methodology. This includes clustering and biclustering of gene-expression data and sample classification.…”

Section: Introductionmentioning

confidence: 99%

bioNMF: a web-based tool for nonnegative matrix factorization in biology

Mejía-Roa

Carmona-Sáez

Nogales

et al. 2008

Nucleic Acids Research

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In the last few years, advances in high-throughput technologies are generating large amounts of biological data that require analysis and interpretation. Nonnegative matrix factorization (NMF) has been established as a very effective method to reveal information about the complex latent relationships in experimental data sets. Using this method as part of the exploratory data analysis, workflow would certainly help in the process of interpreting and understanding the complex biology mechanisms that are underlying experimental data. We have developed bioNMF, a web-based tool that implements the NMF methodology in different analysis contexts to support some of the most important reported applications in biology. This online tool provides a user-friendly interface, combined with a computational efficient parallel implementation of the NMF methods to explore the data in different analysis scenarios. In addition to the online access, bioNMF also provides the same functionality included in the website as a public web services interface, enabling users with more computer expertise to launch jobs into bioNMF server from their own scripts and workflows. bioNMF application is freely available at http://bionmf.dacya.ucm.es.

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“…In essence, NMF aids in the elucidation of localized patterns of similar expression by identifying a small subset of genes that act in a strongly correlated fashion in a subset of the samples. As noted before, such localized patterns may point to groups of co-regulated or functionally relevant genes [38],[43],[47],[48],[50]. For example, groups of genes and samples that show high coefficients for a given metagene (column of W ) and the corresponding metagene expression pattern (row of H ), respectively, may be strongly related in a subset of the data, thus constituting a gene-sample bi-cluster.…”

Section: Parts-based Local Representationmentioning

confidence: 93%

Nonnegative Matrix Factorization: An Analytical and Interpretive Tool in Computational Biology

2008

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In the last decade, advances in high-throughput technologies such as DNA microarrays have made it possible to simultaneously measure the expression levels of tens of thousands of genes and proteins. This has resulted in large amounts of biological data requiring analysis and interpretation. Nonnegative matrix factorization (NMF) was introduced as an unsupervised, parts-based learning paradigm involving the decomposition of a nonnegative matrix V into two nonnegative matrices, W and H, via a multiplicative updates algorithm. In the context of a p×n gene expression matrix V consisting of observations on p genes from n samples, each column of W defines a metagene, and each column of H represents the metagene expression pattern of the corresponding sample. NMF has been primarily applied in an unsupervised setting in image and natural language processing. More recently, it has been successfully utilized in a variety of applications in computational biology. Examples include molecular pattern discovery, class comparison and prediction, cross-platform and cross-species analysis, functional characterization of genes and biomedical informatics. In this paper, we review this method as a data analytical and interpretive tool in computational biology with an emphasis on these applications.

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bioNMF: a versatile tool for non-negative matrix factorization in biology

Cited by 79 publications

References 26 publications

Altered Gene Expression in Morphologically Normal Epithelial Cells from Heterozygous Carriers of BRCA1 or BRCA2 Mutations

Altered Gene Expression in Morphologically Normal Epithelial Cells from Heterozygous Carriers of BRCA1 or BRCA2 Mutations

bioNMF: a web-based tool for nonnegative matrix factorization in biology

Nonnegative Matrix Factorization: An Analytical and Interpretive Tool in Computational Biology

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