PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Fuzzy ensemble clustering for DNA microarray data analysis
Roberto Avogadri and Giorgio Valentini
In: Applications of Fuzzy Sets Theory 10.1007/978-3-540-73400-0_68 , 4578 (4573). (2007) Springer , Berlin, Germany , pp. 537-543. ISBN 978-3-540-73399-7


Two major problems related the unsupervised analysis of gene expression data are represented by the accuracy and reliability of the discovered clusters, and by the biological fact that classes of examples or classes of functionally related genes are sometimes not clearly defined. To face these items, we propose a fuzzy ensemble clustering approach to both improve the accuracy of clustering results and to take into account the inherent fuzziness of biological and bio-medical gene expression data. Preliminary results with DNA microarray data of lymphoma and adenocarcinoma patients show the effectiveness of the proposed approach.

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EPrint Type:Book Section
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Theory & Algorithms
ID Code:3616
Deposited By:Giorgio Valentini
Deposited On:13 February 2008