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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Wolf, T. Brors, B. Hofmann, T. Georgii, E. |
| Copyright Year | 2006 |
| Description | Author affiliation: Dept. of Comput. Sci., TU Darmstadt (Wolf, T.) |
| Abstract | We consider the problem of simultaneously clustering genes and conditions of a gene expression data matrix. A bicluster is defined as a subset of genes that show similar behavior within a subset of conditions. Finding biclusters can be useful for revealing groups of genes involved in the same molecular process as well as groups of conditions where this process takes place. Previous work either deals with local, bicluster-based criteria or assumes a very specific structure of the data matrix (e.g. checkerboard or block-diagonal) (Ryan et al., 2005). In contrast, our goal is to find a set of flexibly arranged biclusters which is optimal in regard to a global objective function. As this is a NP-hard combinatorial problem, we describe several techniques to obtain approximate solutions. We benchmarked our approach successfully on the Alizadeh B-cell lymphoma data set (Alizadeh et al., 2000) |
| Sponsorship | IEEE CPS |
| Starting Page | 125 |
| Ending Page | 129 |
| File Size | 181079 |
| Page Count | 5 |
| File Format | |
| ISBN | 0769527027 |
| DOI | 10.1109/ICDMW.2006.88 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-12-18 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Computer science Text mining Filtering Biological system modeling DNA Collaborative work Large-scale systems Gene expression Intelligent systems Bioinformatics |
| Content Type | Text |
| Resource Type | Article |
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