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BMCBI
2006
183views more  BMCBI 2006»
13 years 8 months ago
Mining gene expression data by interpreting principal components
Background: There are many methods for analyzing microarray data that group together genes having similar patterns of expression over all conditions tested. However, in many insta...
Joseph C. Roden, Brandon W. King, Diane Trout, Ali...
WILF
2007
Springer
147views Fuzzy Logic» more  WILF 2007»
14 years 2 months ago
Fuzzy Ensemble Clustering for DNA Microarray Data Analysis
Two major problems related the unsupervised analysis of gene expression data are represented by the accuracy and reliability of the discovered clusters, and by the biological fact ...
Roberto Avogadri, Giorgio Valentini
IV
2009
IEEE
155views Visualization» more  IV 2009»
14 years 3 months ago
Visualizing Temporal Dynamics at the Genomic and Metabolic Level
We present an application for integrated visualization of gene expression data from time series experiments in gene regulation networks and metabolic networks. Such integration is...
Romain Bourqui, Michel A. Westenberg
BMCBI
2007
173views more  BMCBI 2007»
13 years 8 months ago
Recursive Cluster Elimination (RCE) for classification and feature selection from gene expression data
Background: Classification studies using gene expression datasets are usually based on small numbers of samples and tens of thousands of genes. The selection of those genes that a...
Malik Yousef, Segun Jung, Louise C. Showe, Michael...
BMCBI
2002
195views more  BMCBI 2002»
13 years 8 months ago
Clustering of the SOM easily reveals distinct gene expression patterns: results of a reanalysis of lymphoma study
Background: A method to evaluate and analyze the massive data generated by series of microarray experiments is of utmost importance to reveal the hidden patterns of gene expressio...
Junbai Wang, Jan Delabie, Hans Christian Aasheim, ...