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» Clustering cancer gene expression data: a comparative study
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BMCBI
2008
134views more  BMCBI 2008»
13 years 3 months ago
Clustering cancer gene expression data: a comparative study
Background The use of clustering methods for the discovery of cancer subtypes has drawn a great deal of attention in the scientific community. While bioinformaticians have propose...
Marcílio Carlos Pereira de Souto, Ivan G. C...
IJCNN
2008
IEEE
13 years 10 months ago
Comparative study on normalization procedures for cluster analysis of gene expression datasets
—Normalization before clustering is often needed for proximity indices, such as Euclidian distance, which are sensitive to differences in the magnitude or scales of the attribute...
Marcílio Carlos Pereira de Souto, Daniel S....
BMCBI
2008
166views more  BMCBI 2008»
13 years 3 months ago
Biclustering via optimal re-ordering of data matrices in systems biology: rigorous methods and comparative studies
Background: The analysis of large-scale data sets via clustering techniques is utilized in a number of applications. Biclustering in particular has emerged as an important problem...
Peter A. DiMaggio Jr., Scott R. McAllister, Christ...
APBC
2004
121views Bioinformatics» more  APBC 2004»
13 years 5 months ago
Using Emerging Pattern Based Projected Clustering and Gene Expression Data for Cancer Detection
Using gene expression data for cancer detection is one of the famous research topics in bioinformatics. Theoretically, gene expression data is capable to detect all types of early...
Larry T. H. Yu, Fu-Lai Chung, Stephen Chi-fai Chan...
BMCBI
2005
190views more  BMCBI 2005»
13 years 3 months ago
An Entropy-based gene selection method for cancer classification using microarray data
Background: Accurate diagnosis of cancer subtypes remains a challenging problem. Building classifiers based on gene expression data is a promising approach; yet the selection of n...
Xiaoxing Liu, Arun Krishnan, Adrian Mondry