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» Clustering cancer gene expression data: a comparative study
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IDA
2007
Springer
15 years 6 months ago
An unsupervised clustering approach for leukaemia classification based on DNA micro-arrays data
: DNA micro-arrays provide thousands of genomic expressions on the same subject. A main issue is then to find the subset of genes whose degeneration is responsible of a certain typ...
Simone Garatti, Sergio Bittanti, Diego Liberati, A...
BMCBI
2006
213views more  BMCBI 2006»
15 years 6 months ago
CoXpress: differential co-expression in gene expression data
Background: Traditional methods of analysing gene expression data often include a statistical test to find differentially expressed genes, or use of a clustering algorithm to find...
Michael Watson
KDD
2003
ACM
148views Data Mining» more  KDD 2003»
16 years 6 months ago
A highly-usable projected clustering algorithm for gene expression profiles
Projected clustering has become a hot research topic due to its ability to cluster high-dimensional data. However, most existing projected clustering algorithms depend on some cri...
Kevin Y. Yip, David W. Cheung, Michael K. Ng
BMCBI
2006
171views more  BMCBI 2006»
15 years 6 months ago
The effect of oligonucleotide microarray data pre-processing on the analysis of patient-cohort studies
Background: Intensity values measured by Affymetrix microarrays have to be both normalized, to be able to compare different microarrays by removing non-biological variation, and s...
Roel G. W. Verhaak, Frank J. T. Staal, Peter J. M....
BMCBI
2011
15 years 1 months ago
Appearance frequency modulated gene set enrichment testing
Background: Gene set enrichment testing has helped bridge the gap from an individual gene to a systems biology interpretation of microarray data. Although gene sets are defined a ...
Jun Ma, Maureen A. Sartor, H. V. Jagadish