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» Identifying Objects Using Cluster and Concept Analysis
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BMCBI
2008
146views more  BMCBI 2008»
14 years 9 months ago
A phase synchronization clustering algorithm for identifying interesting groups of genes from cell cycle expression data
Background: The previous studies of genome-wide expression patterns show that a certain percentage of genes are cell cycle regulated. The expression data has been analyzed in a nu...
Chang Sik Kim, Cheol Soo Bae, Hong Joon Tcha
IWPSE
2007
IEEE
15 years 3 months ago
Using concept analysis to detect co-change patterns
Software systems need to change over time to cope with new requirements, and due to design decisions, the changes happen to crosscut the system’s structure. Understanding how ch...
Tudor Gîrba, Stéphane Ducasse, Adrian...
NAR
2008
175views more  NAR 2008»
14 years 9 months ago
Onto-CC: a web server for identifying Gene Ontology conceptual clusters
The Gene Ontology (GO) vocabulary has been extensively explored to analyze the functions of coexpressed genes. However, despite its extended use in Biology and Medical Sciences, t...
Rocío Romero-Záliz, Coral del Val, J...
BMCBI
2004
158views more  BMCBI 2004»
14 years 9 months ago
Incremental genetic K-means algorithm and its application in gene expression data analysis
Background: In recent years, clustering algorithms have been effectively applied in molecular biology for gene expression data analysis. With the help of clustering algorithms suc...
Yi Lu, Shiyong Lu, Farshad Fotouhi, Youping Deng, ...
FUIN
2011
358views Cryptology» more  FUIN 2011»
14 years 28 days ago
Unsupervised and Supervised Learning Approaches Together for Microarray Analysis
In this article, a novel concept is introduced by using both unsupervised and supervised learning. For unsupervised learning, the problem of fuzzy clustering in microarray data as ...
Indrajit Saha, Ujjwal Maulik, Sanghamitra Bandyopa...