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» Fractal Clustering for Microarray Data Analysis
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BIOINFORMATICS
2007
195views more  BIOINFORMATICS 2007»
14 years 9 months ago
Context-dependent clustering for dynamic cellular state modeling of microarray gene expression
Motivation: High-throughput expression profiling allows researchers to study gene activities globally. Genes with similar expression profiles are likely to encode proteins that ma...
Shinsheng Yuan, Ker-Chau Li
BIBE
2004
IEEE
107views Bioinformatics» more  BIBE 2004»
15 years 1 months ago
Enhanced pClustering and Its Applications to Gene Expression Data
Clustering has been one of the most popular methods to discover useful biological insights from DNA microarray. An interesting paradigm is simultaneous clustering of both genes an...
Sungroh Yoon, Christine Nardini, Luca Benini, Giov...
BMCBI
2006
119views more  BMCBI 2006»
14 years 9 months ago
LS-NMF: A modified non-negative matrix factorization algorithm utilizing uncertainty estimates
Background: Non-negative matrix factorisation (NMF), a machine learning algorithm, has been applied to the analysis of microarray data. A key feature of NMF is the ability to iden...
Guoli Wang, Andrew V. Kossenkov, Michael F. Ochs
IDA
2005
Springer
15 years 3 months ago
Biological Cluster Validity Indices Based on the Gene Ontology
With the invention of biotechnological high throughput methods like DNA microarrays and the analysis of the resulting huge amounts of biological data, clustering algorithms gain ne...
Nora Speer, Christian Spieth, Andreas Zell
WABI
2005
Springer
179views Bioinformatics» more  WABI 2005»
15 years 3 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