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WABI
2005
Springer
179views Bioinformatics» more  WABI 2005»
14 years 1 months ago
Spectral Clustering Gene Ontology Terms to Group Genes by Function
Abstract. With the invention of biotechnological high throughput methods like DNA microarrays, biologists are capable of producing huge amounts of data. During the analysis of such...
Nora Speer, Christian Spieth, Andreas Zell
BMCBI
2004
158views more  BMCBI 2004»
13 years 7 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, ...
BIODATAMINING
2008
178views more  BIODATAMINING 2008»
13 years 8 months ago
Clustering-based approaches to SAGE data mining
Serial analysis of gene expression (SAGE) is one of the most powerful tools for global gene expression profiling. It has led to several biological discoveries and biomedical appli...
Haiying Wang, Huiru Zheng, Francisco Azuaje
BMCBI
2007
134views more  BMCBI 2007»
13 years 8 months ago
A framework for significance analysis of gene expression data using dimension reduction methods
Background: The most popular methods for significance analysis on microarray data are well suited to find genes differentially expressed across predefined categories. However, ide...
Lars Halvor Gidskehaug, Endre Anderssen, Arnar Fla...
IMSCCS
2006
IEEE
14 years 1 months ago
Clustering of Gene Expression Data: Performance and Similarity Analysis
Background: DNA Microarray technology is an innovative methodology in experimental molecular biology, which has produced huge amounts of valuable data in the profile of gene expre...
Longde Yin, Chun-Hsi Huang