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» Classification of microarray data using gene networks
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97
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BMCBI
2006
88views more  BMCBI 2006»
15 years 2 months ago
A two-sample Bayesian t-test for microarray data
Background: Determining whether a gene is differentially expressed in two different samples remains an important statistical problem. Prior work in this area has featured the use ...
Richard J. Fox, Matthew W. Dimmic
100
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CSB
2004
IEEE
164views Bioinformatics» more  CSB 2004»
15 years 6 months ago
Biclustering in Gene Expression Data by Tendency
The advent of DNA microarray technologies has revolutionized the experimental study of gene expression. Clustering is the most popular approach of analyzing gene expression data a...
Jinze Liu, Jiong Yang, Wei Wang 0010
EVOW
2004
Springer
15 years 8 months ago
Evolutionary Search of Thresholds for Robust Feature Set Selection: Application to the Analysis of Microarray Data
Abstract. We deal with two important problems in pattern recognition that arise in the analysis of large datasets. While most feature subset selection methods use statistical techn...
Carlos Cotta, Christian Sloper, Pablo Moscato
141
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BMCBI
2007
179views more  BMCBI 2007»
15 years 2 months ago
Transcript-level annotation of Affymetrix probesets improves the interpretation of gene expression data
Background: The wide use of Affymetrix microarray in broadened fields of biological research has made the probeset annotation an important issue. Standard Affymetrix probeset anno...
Hui Yu, Feng Wang, Kang Tu, Lu Xie, Yuan-Yuan Li, ...
122
Voted
CSB
2005
IEEE
133views Bioinformatics» more  CSB 2005»
15 years 8 months ago
Sequential Classification for Microarray and Clinical Data
Sequential classification uses in a stepwise process only part of the data (evidence) for partial classification, i.e., classifying only objects with sufficient evidence and leavi...
Günter Tusch