An Algorithm to Assess the Reliability of Hierarchical Clusters in Gene Expression Data
KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III
A stability-based algorithm to validate hierarchical clusters of genes
International Journal of Knowledge Engineering and Soft Data Paradigms
Biological cluster validity indices based on the gene ontology
IDA'05 Proceedings of the 6th international conference on Advances in Intelligent Data Analysis
Post-processing strategies for improving local gene expression pattern analysis
International Journal of Data Mining and Bioinformatics
| Hi-index | 3.84 |
Summary: In this paper we present a data mining system, which allows the application of different clustering and cluster validity algorithms for DNA microarray data. This tool may improve the quality of the data analysis results, and may support the prediction of the number of relevant clusters in the microarray datasets. This systematic evaluation approach may significantly aid genome expression analyses for knowledge discovery applications. The developed software system may be effectively used for clustering and validating not only DNA microarray expression analysis applications but also other biomedical and physical data with no limitations. Availability: The program is freely available for non-profit use on request at http://www.cs.tcd.ie/Nadia.Bolshakova/Machaon.html Contact: Nadia.Bolshakova@cs.tcd.ie