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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Ando, S. Iba, H. |
| Copyright Year | 2003 |
| Description | Author affiliation: Dept. of Electron. Eng., Tokyo Univ., Japan (Ando, S.; Iba, H.) |
| Abstract | Constructing genetic network model from microarray data is an important approach to understanding the functions of the genes. Proposed in this paper is the use of pair-wise correlation analysis to capture regulation and co-regulation among genes. It considers pair-wise p-metrics correlation between the expression of the genes and also the change in expression of the genes. The method is used alongside meta heuristic approach to construct gene regulatory networks of difference and differential equation model from microarray data. The evolutionary algorithms are used to find the structure of the model with highest criteria. Using the result of the analysis improves the performance of the meta heuristics and allows us to extract relations from gene expression of E. coli and S. cerevisiae. |
| Sponsorship | Air Force Iffice of Sci. Res. Asian Office of Aerospace Res and Development Army Res. Office - Far East CISCO Evoluationary Programming Soc. IEE Inst. of Engineers, Australia IEEE Neural Networks Soc. Univ. of New South Wales |
| Starting Page | 207 |
| Ending Page | 214 |
| File Size | 486834 |
| Page Count | 8 |
| File Format | |
| ISBN | 0780378040 |
| DOI | 10.1109/CEC.2003.1299576 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2003-12-08 |
| Publisher Place | Australia |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Genetic algorithms Pairwise error probability Algorithm design and analysis Gene expression Bayesian methods Data engineering Bioinformatics Power system modeling Predictive models Genetic engineering |
| Content Type | Text |
| Resource Type | Article |
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