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CBMS
2005
IEEE
13 years 11 months ago
An Ontology-Driven Clustering Method for Supporting Gene Expression Analysis
The Gene Ontology (GO) is an important knowledge resource for biologists and bioinformaticians. This paper explores the integration of similarity information derived from GO into ...
Haiying Wang, Francisco Azuaje, Olivier Bodenreide...
BMCBI
2006
203views more  BMCBI 2006»
13 years 5 months ago
Independent component analysis reveals new and biologically significant structures in micro array data
Background: An alternative to standard approaches to uncover biologically meaningful structures in micro array data is to treat the data as a blind source separation (BSS) problem...
Attila Frigyesi, Srinivas Veerla, David Lindgren, ...
BMCBI
2008
200views more  BMCBI 2008»
13 years 5 months ago
Defining functional distances over Gene Ontology
Background: A fundamental problem when trying to define the functional relationships between proteins is the difficulty in quantifying functional similarities, even when well-stru...
Angela del Pozo, Florencio Pazos, Alfonso Valencia
BMCBI
2010
122views more  BMCBI 2010»
13 years 24 days ago
Functional enrichment analyses and construction of functional similarity networks with high confidence function prediction by PF
Background: A new paradigm of biological investigation takes advantage of technologies that produce large high throughput datasets, including genome sequences, interactions of pro...
Troy Hawkins, Meghana Chitale, Daisuke Kihara
BMCBI
2007
166views more  BMCBI 2007»
13 years 5 months ago
How to decide which are the most pertinent overly-represented features during gene set enrichment analysis
Background: The search for enriched features has become widely used to characterize a set of genes or proteins. A key aspect of this technique is its ability to identify correlati...
Roland Barriot, David J. Sherman, Isabelle Dutour