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» Two-phase clustering strategy for gene expression data sets
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77
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BMCBI
2008
126views more  BMCBI 2008»
14 years 9 months ago
Relating gene expression data on two-component systems to functional annotations in Escherichia coli
Background: Obtaining physiological insights from microarray experiments requires computational techniques that relate gene expression data to functional information. Traditionall...
Anne M. Denton, Jianfei Wu, Megan K. Townsend, Pre...
SIGMOD
2002
ACM
132views Database» more  SIGMOD 2002»
15 years 9 months ago
Clustering by pattern similarity in large data sets
Clustering is the process of grouping a set of objects into classes of similar objects. Although definitions of similarity vary from one clustering model to another, in most of th...
Haixun Wang, Wei Wang 0010, Jiong Yang, Philip S. ...
73
Voted
BMCBI
2006
136views more  BMCBI 2006»
14 years 9 months ago
Metric for Measuring the Effectiveness of Clustering of DNA Microarray Expression
Background: The recent advancement of microarray technology with lower noise and better affordability makes it possible to determine expression of several thousand genes simultane...
Raja Loganantharaj, Satish Cheepala, John Clifford
GECCO
2007
Springer
162views Optimization» more  GECCO 2007»
15 years 3 months ago
A multi-objective approach to discover biclusters in microarray data
The main motivation for using a multi–objective evolutionary algorithm for finding biclusters in gene expression data is motivated by the fact that when looking for biclusters ...
Federico Divina, Jesús S. Aguilar-Ruiz
PR
2008
88views more  PR 2008»
14 years 9 months ago
Modified global k
Clustering in gene expression data sets is a challenging problem. Different algorithms for clustering of genes have been proposed. However due to the large number of genes only a ...
Adil M. Bagirov