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» Fractal Clustering for Microarray Data Analysis
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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,...
AUSAI
2005
Springer
15 years 3 months ago
Finding Similar Patterns in Microarray Data
Abstract. In this paper we propose a clustering algorithm called sCluster for analysis of gene expression data based on pattern-similarity. The algorithm captures the tight cluster...
Xiangsheng Chen, Jiuyong Li, Grant Daggard, Xiaodi...
SAC
2006
ACM
15 years 3 months ago
Two-phase clustering strategy for gene expression data sets
In the context of genome research, the method of gene expression analysis has been used for several years. Related microarray experiments are conducted all over the world, and con...
Dirk Habich, Thomas Wächter, Wolfgang Lehner,...
CSDA
2008
128views more  CSDA 2008»
14 years 9 months ago
Assessing agreement of clustering methods with gene expression microarray data
In the rapidly evolving field of genomics, many clustering and classification methods have been developed and employed to explore patterns in gene expression data. Biologists face...
Xueli Liu, Sheng-Chien Lee, George Casella, Gary F...
BMCBI
2008
204views more  BMCBI 2008»
14 years 9 months ago
EST2uni: an open, parallel tool for automated EST analysis and database creation, with a data mining web interface and microarra
Background: Expressed sequence tag (EST) collections are composed of a high number of single-pass, redundant, partial sequences, which need to be processed, clustered, and annotat...
Javier Forment, Francisco Gilabert Villamón...