A stability-based algorithm to validate hierarchical clusters of genes Online publication date: Mon, 19-Oct-2009
by Roberto Avogadri, Matteo Brioschi, Fulvia Ferrazzi, Matteo Re, Alessandro Beghini, Giorgio Valentini
International Journal of Knowledge Engineering and Soft Data Paradigms (IJKESDP), Vol. 1, No. 4, 2009
Abstract: Stability-based methods have been successfully applied in functional genomics to the analysis of the reliability of clusterings characterised by a relatively low number of examples and clusters. The application of these methods to the validation of gene clusters discovered in biomolecular data may lead to computational problems due to the large amount of possible clusters involved. To address this problem, we present a stability-based algorithm to discover significant clusters in hierarchical clusterings with a large number of examples and clusters. The reliability of clusters of genes discovered in gene expression data of patients affected by human myeloid leukaemia is analysed through the proposed algorithm, and their relationships with specific biological processes are tested by means of Gene Ontology-based functional enrichment methods.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Knowledge Engineering and Soft Data Paradigms (IJKESDP):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook