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BMCBI
2007
173views more  BMCBI 2007»
13 years 7 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 7 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, ...
BMCBI
2010
92views more  BMCBI 2010»
13 years 7 months ago
Integrating gene expression and GO classification for PCA by preclustering
Background: Gene expression data can be analyzed by summarizing groups of individual gene expression profiles based on GO annotation information. The mean expression profile per g...
Jorn R. de Haan, Ester Piek, René C. van Sc...
BMCBI
2008
115views more  BMCBI 2008»
13 years 7 months ago
Principal components analysis based methodology to identify differentially expressed genes in time-course microarray data
Background: Time-course microarray experiments are being increasingly used to characterize dynamic biological processes. In these experiments, the goal is to identify genes differ...
Sudhakar Jonnalagadda, Rajagopalan Srinivasan
CSB
2005
IEEE
156views Bioinformatics» more  CSB 2005»
14 years 29 days ago
A Robust Meta-classification Strategy for Cancer Diagnosis from Gene Expression Data
One of the major challenges in cancer diagnosis from microarray data is to develop robust classification models which are independent of the analysis techniques used and can combi...
Gabriela Alexe, Gyan Bhanot, Babu Venkataraghavan,...