Journal article
GE-Miner: integration of cluster ensemble and text mining for comprehensive gene expression analysis
International journal of bioinformatics research and applications, v 2(3), pp 325-338
2006
PMID: 18048169
Abstract
Generating high quality gene clusters and identifying the underlying biological mechanism of the gene clusters are the important goals of clustering gene expression analysis. Based on this consideration, we design and develop a unified system Gene Expression Miner (GE-Miner) by integrating cluster ensemble, text clustering and multidocument summarisation and provide an environment for comprehensive gene expression data analysis. Experimental results demonstrate that our systems can obtain high quality clusters and provide concise and informative textual summary for the gene clusters.
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1 citations in Scopus
Details
- Title
- GE-Miner: integration of cluster ensemble and text mining for comprehensive gene expression analysis
- Creators
- Xiaohua Hu - Drexel University
- Publication Details
- International journal of bioinformatics research and applications, v 2(3), pp 325-338
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Information Science
- Scopus ID
- 2-s2.0-33748805558
- Other Identifier
- 991019173983404721