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RECOMB
2010
Springer
13 years 11 months ago
Hierarchical Generative Biclustering for MicroRNA Expression Analysis
Clustering methods are a useful and common first step in gene expression studies, but the results may be hard to interpret. We bring in explicitly an indicator of which genes tie ...
José Caldas, Samuel Kaski
CSB
2004
IEEE
173views Bioinformatics» more  CSB 2004»
13 years 8 months ago
Gene Ontology Friendly Biclustering of Expression Profiles
The soundness of clustering in the analysis of gene expression profiles and gene function prediction is based on the hypothesis that genes with similar expression profiles may imp...
Jinze Liu, Wei Wang 0010, Jiong Yang
BMCBI
2008
166views more  BMCBI 2008»
13 years 4 months ago
Biclustering via optimal re-ordering of data matrices in systems biology: rigorous methods and comparative studies
Background: The analysis of large-scale data sets via clustering techniques is utilized in a number of applications. Biclustering in particular has emerged as an important problem...
Peter A. DiMaggio Jr., Scott R. McAllister, Christ...
IADIS
2008
13 years 6 months ago
Sisa: Seeded Iterative Signature Algorithm for Biclustering Gene Expression Data
One approach to reduce the complexity of the task in the analysis of large scale genome-wide expression is to group the genes showing similar expression patterns into what are cal...
Neelima Gupta, Seema Aggarwal
BMCBI
2006
170views more  BMCBI 2006»
13 years 4 months ago
Biclustering of gene expression data by non-smooth non-negative matrix factorization
Background: The extended use of microarray technologies has enabled the generation and accumulation of gene expression datasets that contain expression levels of thousands of gene...
Pedro Carmona-Saez, Roberto D. Pascual-Marqui, Fra...