How well do we understand the clusters found in microarray data?

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dc.contributor.author Clare, Amanda
dc.contributor.author King, Ross Donald
dc.date.accessioned 2006-04-25T15:59:11Z
dc.date.available 2006-04-25T15:59:11Z
dc.date.issued 2002
dc.identifier.citation Clare , A & King , R D 2002 , ' How well do we understand the clusters found in microarray data? ' In Silico Biology , vol 2 , no. 4 , pp. 511-522 . en
dc.identifier.issn 1434-3207
dc.identifier.other PURE: 68573
dc.identifier.other dspace: 2160/159
dc.identifier.uri http://hdl.handle.net/2160/159
dc.identifier.uri http://www.bioinfo.de/isb/2002020046/ en
dc.description Clare, A. and King R.D. (2002) How well do we understand the clusters found in microarray data? In In Silico Biol. 2, 0046 en
dc.description.abstract We wished to quantify the state-of-the-art of our understanding of clusters in microarray data. To do this we systematically compared the clusters produced on sets of microarray data using a representative set of clustering algorithms (hierarchical, k-means, and a modified version of QT_CLUST) with the annotation schemes MIPS, GeneOntology and GenProtEC. We assumed that if a cluster reflected known biology its members would share related ontological annotations. This assumption is the basis of 'guilt-by-association' and is commonly used to assign the putative function of proteins. To statistically measure the relationship between cluster and annotation we developed a new predictive discriminatory measure. We found that the clusters found in microarray data do not in general agree with functional annotation classes. Although many statistically significant relationships can be found, the majority of clusters are not related to known biology (as described in annotation ontologies). This implies that use of guilt-by-association is not supported by annotation ontologies. Depending on the estimate of the amount of noise in the data, our results suggest that bioinformatics has only codified a small proportion of the biological knowledge required to understand microarray data. The annotated clusters can be found at http://www.aber.ac.uk/compsci/Research/bio/dss/gba/. en
dc.language.iso eng
dc.relation.ispartof In Silico Biology en
dc.title How well do we understand the clusters found in microarray data? en
dc.type Text en
dc.type.publicationtype Article (Journal) en
dc.contributor.institution Department of Computer Science en
dc.contributor.institution Bioinformatics and Computational Biology Group en
dc.description.status Peer reviewed en


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