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» Clustering of Gene Expression Data: Performance and Similari...
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TCBB
2010
136views more  TCBB 2010»
14 years 8 months ago
Integrating Data Clustering and Visualization for the Analysis of 3D Gene Expression Data
— The recent development of methods for extracting precise measurements of spatial gene expression patterns from three-dimensional (3D) image data opens the way for new analyses ...
Oliver Rübel, Gunther H. Weber, Min-Yu Huang,...
JIFS
2002
134views more  JIFS 2002»
14 years 9 months ago
Classification of gene expression data using fuzzy logic
Microarray technologies have allowed the measurement of expression of multiple genes simultaneously. Gene expression levels can be used to classify tissues into diagnostic or progn...
Lucila Ohno-Machado, Staal A. Vinterbo, Griffin We...
BMCBI
2010
153views more  BMCBI 2010»
14 years 9 months ago
Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering
Background: Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or su...
Eva Freyhult, Mattias Landfors, Jenny Önskog,...
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...
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