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» Integrating Microarray Data by Consensus Clustering
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CBMS
2006
IEEE
13 years 11 months ago
Incorporating Gene Ontology in Clustering Gene Expression Data
In this paper we consider a general framework for clustering expression data that permits integration of various biological data sources through combination of corresponding dissi...
Rafal Kustra, Adam Zagdanski
FUIN
2011
358views Cryptology» more  FUIN 2011»
13 years 1 months ago
Unsupervised and Supervised Learning Approaches Together for Microarray Analysis
In this article, a novel concept is introduced by using both unsupervised and supervised learning. For unsupervised learning, the problem of fuzzy clustering in microarray data as ...
Indrajit Saha, Ujjwal Maulik, Sanghamitra Bandyopa...
BIBE
2007
IEEE
153views Bioinformatics» more  BIBE 2007»
13 years 11 months ago
Combined expression data with missing values and gene interaction network analysis: a Markovian integrated approach
—DNA microarray technologies provide means for monitoring in the order of tens of thousands of gene expression levels quantitatively and simultaneously. However data generated in...
Juliette Blanchet, Matthieu Vignes
BMCBI
2007
123views more  BMCBI 2007»
13 years 10 months ago
Heritable clustering and pathway discovery in breast cancer integrating epigenetic and phenotypic data
Background: In order to recapitulate tumor progression pathways using epigenetic data, we developed novel clustering and pathway reconstruction algorithms, collectively referred t...
Zailong Wang, Pearlly Yan, Dustin P. Potter, Chari...
BMCBI
2004
208views more  BMCBI 2004»
13 years 9 months ago
Hybrid clustering for microarray image analysis combining intensity and shape features
Background: Image analysis is the first crucial step to obtain reliable results from microarray experiments. First, areas in the image belonging to single spots have to be identif...
Jörg Rahnenführer, Daniel Bozinov