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» Two-phase clustering strategy for gene expression data sets
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BMCBI
2010
112views more  BMCBI 2010»
14 years 9 months ago
PhenoFam-gene set enrichment analysis through protein structural information
Background: With the current technological advances in high-throughput biology, the necessity to develop tools that help to analyse the massive amount of data being generated is e...
Maciej Paszkowski-Rogacz, Mikolaj Slabicki, M. Ter...
95
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GECCO
2003
Springer
127views Optimization» more  GECCO 2003»
15 years 2 months ago
Complex Function Sets Improve Symbolic Discriminant Analysis of Microarray Data
Abstract. Our ability to simultaneously measure the expression levels of thousands of genes in biological samples is providing important new opportunities for improving the diagnos...
David M. Reif, Bill C. White, Nancy Olsen, Thomas ...
KDD
2002
ACM
147views Data Mining» more  KDD 2002»
15 years 10 months ago
Visualized Classification of Multiple Sample Types
The goal of the knowledge discovery and data mining is to extract the useful knowledge from the given data. Visualization enables us to find structures, features, patterns, and re...
Li Zhang, Aidong Zhang, Murali Ramanathan
BMCBI
2007
149views more  BMCBI 2007»
14 years 9 months ago
Novel and simple transformation algorithm for combining microarray data sets
Background: With microarray technology, variability in experimental environments such as RNA sources, microarray production, or the use of different platforms, can cause bias. Suc...
Ki-Yeol Kim, Dong Hyuk Ki, Ha Jin Jeong, Hei-Cheul...
BMCBI
2008
96views more  BMCBI 2008»
14 years 9 months ago
Use of normalization methods for analysis of microarrays containing a high degree of gene effects
Background: High-throughput microarrays are widely used to study gene expression across tissues and developmental stages. Analysis of gene expression data is challenging in these ...
Terri T. Ni, William J. Lemon, Yu Shyr, Tao P. Zho...