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

Background: In the Bioinformatics field, a great deal of interest has been given to Non-negative matrix factorization technique (NMF), due to its capability of providing new insights and relevant information about the complex latent relationships in experimental data sets. This method, and some of its variants, has been successfully applied to gene expression, sequence analysis, functional characterization of genes and text mining. Even if the interest on this technique by the bioinformatics community has been increased during the last few years, there are not many available simple standalone tools to specifically perform these types of data analysis in an integrated environment. Results: In this work we propose a versatile and user-friendly tool that implements the NMF methodology in different analysis contexts to support some of the most important reported applications of this new methodology. This includes clustering and biclustering gene expression data, protein sequence analysis,...

• Type: Journal
• Year: 2006
• Where: BMCBI
• Authors: Alberto D. Pascual-Montano, Pedro Carmona-Saez, Monica Chagoyen, Francisco Tirado, José María Carazo, Roberto D. Pascual-Marqui
• Keywords: Bioinformatics Field, BMCBI 2006, Sequence Analysis, Text Mining