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- Title
INTEGRATING MICROARRAY DATA BY CONSENSUS CLUSTERING.
- Authors
Filkov, Vladimir; Skiena, Steven
- Abstract
With the exploding volume of microarray experiments comes increasing interest in mining repositories of such data. Meaningfully combining results from varied experiments on an equal basis is a challenging task. Here we propose a general method for integrating heterogeneous data sets based on the consensus clustering formalism. Our method analyzes source-specific clusterings and identifies a consensus set-partition which is as close as possible to all of them. We develop a general criterion to assess the potential benefit of integrating multiple heterogeneous data sets, i.e. whether the integrated data is more informative than the individual data sets. We apply our methods on two popular sets of microarray data yielding gene classifications of potentially greater interest than could be derived from the analysis of each individual data set.
- Subjects
COMPUTER peripherals; ELECTRONIC data processing; HETEROGENEOUS computing; INFORMATION storage &; retrieval systems; CONLAN (Computer hardware description language); CLASSIFICATION
- Publication
International Journal on Artificial Intelligence Tools, 2004, Vol 13, Issue 4, p863
- ISSN
0218-2130
- Publication type
Article
- DOI
10.1142/S0218213004001867