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Fuzzy ensemble clustering for DNA microarray data analysis
| Content Provider | CiteSeerX |
|---|---|
| Author | Avogadri, Roberto Valentini, Giorgio |
| Abstract | Abstract. 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. 1 |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Dna Microarray Data Analysis Fuzzy Ensemble Clustering Unsupervised Analysis Gene Expression Data Biological Fact Inherent Fuzziness Bio-medical Gene Expression Data Dna Microarray Data Discovered Cluster Adenocarcinoma Patient |
| Content Type | Text |
| Resource Type | Article |
