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» Evaluation of clustering algorithms for gene expression data
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ICDE
2009
IEEE
155views Database» more  ICDE 2009»
16 years 3 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
AIME
2007
Springer
15 years 7 months ago
Interpreting Gene Expression Data by Searching for Enriched Gene Sets
This paper presents a novel method integrating gene-gene interaction information and Gene Ontology for the construction of new gene sets that are potentially enriched. Enrichment o...
Igor Trajkovski, Nada Lavrac
BMCBI
2010
155views more  BMCBI 2010»
15 years 1 months ago
A bi-ordering approach to linking gene expression with clinical annotations in gastric cancer
Background: In the study of cancer genomics, gene expression microarrays, which measure thousands of genes in a single assay, provide abundant information for the investigation of...
Fan Shi, Christopher Leckie, Geoff MacIntyre, Izha...
BMCBI
2006
157views more  BMCBI 2006»
15 years 1 months ago
Determination of the minimum number of microarray experiments for discovery of gene expression patterns
Background: One type of DNA microarray experiment is discovery of gene expression patterns for a cell line undergoing a biological process over a series of time points. Two import...
Fang-Xiang Wu, W. J. Zhang, Anthony J. Kusalik
KDD
2003
ACM
190views Data Mining» more  KDD 2003»
16 years 1 months ago
Distance-enhanced association rules for gene expression
We introduce a novel data mining technique for the analysis of gene expression. Gene expression is the effective production of the protein that a gene encodes. We focus on the cha...
Aleksandar Icev, Carolina Ruiz, Elizabeth F. Ryder