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BIBE
2007
IEEE
153views Bioinformatics» more  BIBE 2007»
13 years 9 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
135views more  BMCBI 2007»
13 years 8 months ago
Measuring similarities between gene expression profiles through new data transformations
Background: Clustering methods are widely used on gene expression data to categorize genes with similar expression profiles. Finding an appropriate (dis)similarity measure is crit...
Kyungpil Kim, Shibo Zhang, Keni Jiang, Li Cai, In-...
BMCBI
2008
158views more  BMCBI 2008»
13 years 8 months ago
Analyzing M-CSF dependent monocyte/macrophage differentiation: Expression modes and meta-modes derived from an independent compo
Background: The analysis of high-throughput gene expression data sets derived from microarray experiments still is a field of extensive investigation. Although new approaches and ...
Dominik Lutter, Peter Ugocsai, Margot Grandl, Evel...
KDD
2003
ACM
152views Data Mining» more  KDD 2003»
14 years 8 months ago
Interactive exploration of coherent patterns in time-series gene expression data
Discovering coherent gene expression patterns in time-series gene expression data is an important task in bioinformatics research and biomedical applications. In this paper, we pr...
Daxin Jiang, Jian Pei, Aidong Zhang
BMCBI
2011
12 years 11 months ago
Clustering gene expression data with a penalized graph-based metric
Background: The search for cluster structure in microarray datasets is a base problem for the so-called “-omic sciences”. A difficult problem in clustering is how to handle da...
Ariel E. Bayá, Pablo M. Granitto