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» Clustering cancer gene expression data: a comparative study
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BMCBI
2004
113views more  BMCBI 2004»
15 years 6 months ago
Influence of microarrays experiments missing values on the stability of gene groups by hierarchical clustering
Background: Microarray technologies produced large amount of data. The hierarchical clustering is commonly used to identify clusters of co-expressed genes. However, microarray dat...
Alexandre G. de Brevern, Serge A. Hazout, Alain Ma...
BMCBI
2008
128views more  BMCBI 2008»
15 years 5 months ago
In silico analysis of expressed sequence tags from Trichostrongylus vitrinus (Nematoda): comparison of the automated ESTExplorer
Background: The analysis of expressed sequence tags (EST) offers a rapid and cost effective approach to elucidate the transcriptome of an organism, but requires several computatio...
Shivashankar H. Nagaraj, Robin B. Gasser, Alasdair...
BIOINFORMATICS
2005
151views more  BIOINFORMATICS 2005»
15 years 6 months ago
Differential and trajectory methods for time course gene expression data
Motivation: The issue of high dimensionality in microarray data has been, and remains, a hot topic in statistical and computational analysis. Efficient gene filtering and differen...
Yulan Liang, Bamidele Tayo, Xueya Cai, Arpad Kelem...
BIODATAMINING
2008
135views more  BIODATAMINING 2008»
15 years 6 months ago
Fast Gene Ontology based clustering for microarray experiments
Background: Analysis of a microarray experiment often results in a list of hundreds of diseaseassociated genes. In order to suggest common biological processes and functions for t...
Kristian Ovaska, Marko Laakso, Sampsa Hautaniemi
AINA
2008
IEEE
16 years 23 days ago
Missing Value Estimation for Time Series Microarray Data Using Linear Dynamical Systems Modeling
The analysis of gene expression time series obtained from microarray experiments can be effectively exploited to understand a wide range of biological phenomena from the homeostat...
Connie Phong, Raul Singh