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BMCBI
2008
121views more  BMCBI 2008»
14 years 9 months ago
Stability of gene contributions and identification of outliers in multivariate analysis of microarray data
Background: Multivariate ordination methods are powerful tools for the exploration of complex data structures present in microarray data. These methods have several advantages com...
Florent Baty, Daniel Jaeger, Frank Preiswerk, Mart...
FUIN
2011
358views Cryptology» more  FUIN 2011»
14 years 1 months ago
Unsupervised and Supervised Learning Approaches Together for Microarray Analysis
In this article, a novel concept is introduced by using both unsupervised and supervised learning. For unsupervised learning, the problem of fuzzy clustering in microarray data as ...
Indrajit Saha, Ujjwal Maulik, Sanghamitra Bandyopa...
BMCBI
2005
121views more  BMCBI 2005»
14 years 9 months ago
Comparison of seven methods for producing Affymetrix expression scores based on False Discovery Rates in disease profiling data
Background: A critical step in processing oligonucleotide microarray data is combining the information in multiple probes to produce a single number that best captures the express...
Kerby Shedden, Wei Chen, Rork Kuick, Debashis Ghos...
WCE
2007
14 years 10 months ago
Gene Selection for Tumor Classification Using Microarray Gene Expression Data
– In this paper we perform a t-test for significant gene expression analysis in different dimensions based on molecular profiles from microarray data, and compare several computa...
Krishna Yendrapalli, Ram B. Basnet, Srinivas Mukka...
CBMS
2005
IEEE
15 years 3 months ago
An Ontology-Driven Clustering Method for Supporting Gene Expression Analysis
The Gene Ontology (GO) is an important knowledge resource for biologists and bioinformaticians. This paper explores the integration of similarity information derived from GO into ...
Haiying Wang, Francisco Azuaje, Olivier Bodenreide...