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» Identifying Clusters from Positive Data
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BMCBI
2007
173views more  BMCBI 2007»
14 years 9 months ago
Recursive Cluster Elimination (RCE) for classification and feature selection from gene expression data
Background: Classification studies using gene expression datasets are usually based on small numbers of samples and tens of thousands of genes. The selection of those genes that a...
Malik Yousef, Segun Jung, Louise C. Showe, Michael...
64
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SDM
2007
SIAM
86views Data Mining» more  SDM 2007»
14 years 11 months ago
Identifying Bundles of Product Options using Mutual Information Clustering
Mass-produced goods tend to be highly standardized in order to maximize manufacturing efficiencies. Some high-value goods with limited production quantities remain much less stand...
Claudia Perlich, Saharon Rosset
GECCO
2006
Springer
152views Optimization» more  GECCO 2006»
15 years 1 months ago
Using genetic programming to classify node positive patients in bladder cancer
Nodal staging has been identified as an independent indicator of prognosis. Quantitative RT-PCR data was taken for 70 genes associated with bladder cancer and genetic programming ...
Arpit A. Almal, Anirban P. Mitra, Ram H. Datar, Pe...
BMCBI
2005
140views more  BMCBI 2005»
14 years 9 months ago
Dissecting systems-wide data using mixture models: application to identify affected cellular processes
Background: Functional analysis of data from genome-scale experiments, such as microarrays, requires an extensive selection of differentially expressed genes. Under many condition...
J. Peter Svensson, Renée X. de Menezes, Ing...
BMCBI
2008
136views more  BMCBI 2008»
14 years 9 months ago
GPAT: Retrieval of genomic annotation from large genomic position datasets
Background: Recent genome wide transcription factor binding site or chromatin modification mapping analysis techniques, such as chromatin immunoprecipitation (ChIP) linked to DNA ...
Arnaud Krebs, Mattia Frontini, Làszlò...