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

Alberto Pascual-Montano, Pedro Carmona-Saez, Monica Chagoyen, Francisco Tirado, Jose M Carazo, Roberto D Pascual-Marqui
2006 BMC Bioinformatics  
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  ...  Conclusion: bioNMF is a standalone versatile application which does not require any special installation or libraries.  ...  PCS is recipient of a grant from CAM. APM acknowledges the support of the Spanish Ramón y Cajal program.  ... 
doi:10.1186/1471-2105-7-366 pmid:16875499 pmcid:PMC1550731 fatcat:5tyxoqbuezbfjbgaq6dg6xjvgy

Low-Rank Reorganization via Proportional Hazards Non-negative Matrix Factorization Unveils Survival Associated Gene Clusters [article]

Zhi Huang, Paul Salama, Wei Shao, Jie Zhang, Kun Huang
2020 arXiv   pre-print
focused separately on non-negative matrix factorization (NMF) of the gene expression data matrix and survival regression with Cox proportional hazards model.  ...  Though significant effort has been committed to harness gene expression data for multiple analyses while accounting for time-to-event modeling by including survival times, many traditional analyses have  ...  Pascual-Montano, A.; Carmona-Saez, P.; Chagoyen, M.; Tirado, F.; Carazo, J. M.; and Pascual-Marqui, R. D. 2006. bioNMF: a versatile tool for non-negative matrix factorization in biology.  ... 
arXiv:2008.03776v2 fatcat:5tj3om5utvaohi3lfdyc55oivy

Decomposition of brain diffusion imaging data uncovers latent schizophrenias with distinct patterns of white matter anisotropy

Javier Arnedo, Daniel Mamah, David A. Baranger, Michael P. Harms, Deanna M. Barch, Dragan M. Svrakic, Gabriel A. de Erausquin, C. Robert Cloninger, Igor Zwir
2015 NeuroImage  
: a versatile tool for non-negative matrix factorization Poudel, G.R., Stout, J.C., Dominguez, D.J., Churchyard, A., Chua, P., Egan, G.F., Georgiou- Karistianis, N., 2015.  ...  GFM appropriately assembles a 34 collection of unsupervised techniques with Non-negative Matrix Factorization to generate biclusters, rather 35 than averaging across all subjects and all their characteristics  ... 
doi:10.1016/j.neuroimage.2015.06.083 pmid:26151103 fatcat:u2txlaieqzcfbip5xjgqqgq4aa

Genomic Taxonomy Boost by Lexical Clustering

Kosi Gramatikoff
2014 Journal of Investigative Genomics  
The methodology is versatile for clustering methods such as classical hierarchical clustering, as well as non-negative matrix factorization.  ...  Such profiles can be used to infer relationships between texts or between biological sequences, and we demonstrate that two statistical techniques-hierarchical clustering (HC) and non-negative matrix factorization  ...  Acknowledgement This work was partially funded by Australian Research Council grant DP1095849, and KG and JWS were supported by the NIH National Technology Center for Networks and Pathways (grant US4RR020843  ... 
doi:10.15406/jig.2014.01.00004 fatcat:7ycrl6ghsbckpnodey2djaqv6y