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BIOINFORMATICS
2004
119views more  BIOINFORMATICS 2004»
14 years 9 months ago
Analysis of variance components in gene expression data
Motivation: A microarray experiment is a multi-step process, and each step is a potential source of variation. There are two major sources of variation: biological variation and t...
James J. Chen, Robert R. Delongchamp, Chen-An Tsai...
BMCBI
2004
143views more  BMCBI 2004»
14 years 9 months ago
Comparing functional annotation analyses with Catmap
Background: Ranked gene lists from microarray experiments are usually analysed by assigning significance to predefined gene categories, e.g., based on functional annotations. Tool...
Thomas Breslin, Patrik Edén, Morten Krogh
BMCBI
2002
195views more  BMCBI 2002»
14 years 9 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, ...
BICOB
2009
Springer
14 years 7 months ago
A Biclustering Method to Discover Co-regulated Genes Using Diverse Gene Expression Datasets
We propose a two-step biclustering approach to mine co-regulation patterns of a given reference gene to discover other genes that function in a common biological process. Currently...
Doruk Bozdag, Jeffrey D. Parvin, Ümit V. &Cce...
ICDM
2009
IEEE
139views Data Mining» more  ICDM 2009»
15 years 4 months ago
A Bootstrap Approach to Eigenvalue Correction
—Eigenvalue analysis is an important aspect in many data modeling methods. Unfortunately, the eigenvalues of the sample covariance matrix (sample eigenvalues) are biased estimate...
Anne Hendrikse, Luuk J. Spreeuwers, Raymond N. J. ...