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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Qinghua Huang Minhua Lu Hong Yan |
| Copyright Year | 2008 |
| Description | Author affiliation: Dept. of Electron. Eng., City Univ. of Hong Kong, Hong Kong (Qinghua Huang) |
| Abstract | The analysis of gene expression data of breast cancer is important for discovering the signatures that can classify different subtypes of tumors and predict prognosis. Biclustering algorithms have been proven to be able to group the genes with similar expression patterns under a number of samples and offer the capability to analyze the microarray data of cancer. In this study, we propose a new biclustering algorithm which uses an evolutionary search procedure. The algorithm is applied to the conditions to search for combinations of conditions for a potential bicluster. Preliminary results using synthetic and real yeast data sets demonstrate that our algorithm outperforms several existing ones. We have also applied the method to real microarray data sets of breast cancer, and successfully found several biclusters, which can be used as signatures for differentiating tumor types. |
| Starting Page | 829 |
| Ending Page | 834 |
| File Size | 226791 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424418220 |
| DOI | 10.1109/CEC.2008.4630892 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-06-01 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Additives Evolutionary computation Breast cancer Algorithm design and analysis Mathematical model Classification algorithms Gene expression |
| Content Type | Text |
| Resource Type | Article |
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