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» Evaluation of clustering algorithms for gene expression data
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KDD
2002
ACM
145views Data Mining» more  KDD 2002»
16 years 7 months ago
Handling very large numbers of association rules in the analysis of microarray data
The problem of analyzing microarray data became one of important topics in bioinformatics over the past several years, and different data mining techniques have been proposed for ...
Alexander Tuzhilin, Gediminas Adomavicius
CMSB
2006
Springer
15 years 10 months ago
Regulatory Network Reconstruction Using Stochastic Logical Networks
Abstract. This paper presents a method for regulatory network reconstruction from experimental data. We propose a mathematical model for regulatory interactions, based on the work ...
Bartek Wilczynski, Jerzy Tiuryn
157
Voted
BMCBI
2010
115views more  BMCBI 2010»
15 years 6 months ago
Assessment and optimisation of normalisation methods for dual-colour antibody microarrays
Background: Recent advances in antibody microarray technology have made it possible to measure the expression of hundreds of proteins simultaneously in a competitive dual-colour a...
Martin Sill, Christoph Schroder, Jörg D. Hohe...
ICML
2004
IEEE
16 years 7 months ago
K-means clustering via principal component analysis
Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...
Chris H. Q. Ding, Xiaofeng He
GECCO
2003
Springer
127views Optimization» more  GECCO 2003»
15 years 11 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 ...