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» Clustering gene expression patterns
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BMCBI
2008
148views more  BMCBI 2008»
14 years 10 months ago
Discovering biclusters in gene expression data based on high-dimensional linear geometries
Background: In DNA microarray experiments, discovering groups of genes that share similar transcriptional characteristics is instrumental in functional annotation, tissue classifi...
Xiangchao Gan, Alan Wee-Chung Liew, Hong Yan
CSB
2004
IEEE
164views Bioinformatics» more  CSB 2004»
15 years 1 months ago
Biclustering in Gene Expression Data by Tendency
The advent of DNA microarray technologies has revolutionized the experimental study of gene expression. Clustering is the most popular approach of analyzing gene expression data a...
Jinze Liu, Jiong Yang, Wei Wang 0010
ICDE
2009
IEEE
155views Database» more  ICDE 2009»
15 years 11 months ago
Finding Time-Lagged 3D Clusters
Existing 3D clustering algorithms on gene ? sample ? time expression data do not consider the time lags between correlated gene expression patterns. Besides, they either ignore the...
Xin Xu, Ying Lu, Kian-Lee Tan, Anthony K. H. Tung
BMCBI
2011
14 years 4 months ago
Statistical Test of Expression Pattern (STEPath): a new strategy to integrate gene expression data with genomic information in i
Background: In the last decades, microarray technology has spread, leading to a dramatic increase of publicly available datasets. The first statistical tools developed were focuse...
Paolo G. V. Martini, Davide Risso, Gabriele Sales,...
EVOW
2005
Springer
15 years 3 months ago
Order Preserving Clustering over Multiple Time Course Experiments
Abstract. Clustering still represents the most commonly used technique to analyze gene expression data—be it classical clustering approaches that aim at finding biologically rel...
Stefan Bleuler, Eckart Zitzler