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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Forghany, Z. Davarynejad, M. Snaar-Jagalska, B.E. |
| Copyright Year | 2012 |
| Description | Author affiliation: Gorlaeus Laboratory, Institute of Biology, Leiden University, The Netherlands (Forghany, Z.; Snaar-Jagalska, B.E.) || Systems Engineering Section, Faculty of Technology, Policy and Management, Delft University of Technology, The Netherlands (Davarynejad, M.) |
| Abstract | Gene association/interaction networks have complex structures that provide a better understanding of mechanisms at the molecular level that govern essential processes inside the cell. The interaction mechanisms are conventionally modeled by nonlinear dynamic systems of coupled differential equations (S-systems) adhering to the power-law formalism. Our implementation adopts an S-system that is rich enough in structure to capture the dynamics of the gene regulatory networks (GRN) of interest. A comparison of three widely used population-based techniques, namely evolutionary algorithms (EAs), local best particle swarm optimization (PSO) with random topology, and artificial bee colony (ABC) are performed in this study to rapidly identify a solution to inverse problem of GRN reconstruction for understanding the dynamics of the underlying system. A simple yet effective modification of the ABC algorithm, shortly ABC* is proposed as well and tested on the GRN problem. Simulation results on two small-size and a medium size hypothetical gene regulatory networks confirms that the proposed ABC* is superior to all other search schemes studied here. |
| Starting Page | 1 |
| Ending Page | 6 |
| File Size | 897700 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781467315104 |
| e-ISBN | 9781467315098 |
| e-ISBN | 9781467315081 |
| DOI | 10.1109/CEC.2012.6256461 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-06-10 |
| Publisher Place | Australia |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Mathematical model Topology Particle swarm optimization Genetics Computer architecture Optimization |
| Content Type | Text |
| Resource Type | Article |
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