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| Title: | A general recurrent neural network approach to model genetic regulatory networks | |
| Author (s): | Xiao Hu Maglia, Anne Wunsch, Donald C. | |
| Department/Lab Affiliations: | Applied Computational Intelligence Laboratory Biological Sciences Electrical and Computer Engineering | |
| Issue Date: | 2005 | |
| Publisher: | Institute of Electrical and Electronics Engineers | |
| Citation: | Xiao Hu; Maglia, A.; Wunsch, D.C. "A General Recurrent Neural Network A pp.oach to Model Genetic Regulatory Networks" IEEE-EMBS 2005. 27th Annual International Conference of the Engineering in Medicine and Biology Society, 2005. 01-04 Sept. 2005 Pages: 4735- 4738 | |
| Abstract: | There is an urgent need for tools to unravel the complex interactions and functionalities of genes. As such, there has been much interest in reverse-engineering genetic regulatory networks from time series gene expression data. We use an artificial neural network to model the dynamics of complicated gene networks and to learn their parameters. The positive and negative regulations of genes are defined by a weight matrix, and different genes are allowed to have different decaying time constants. We demonstrate the effectiveness of the method by recreating the SOS DNA Repair network of Escherichia coli bacterium, previously discovered through experimental data. | |
| Type: | Article - Conference proceedings text | |
| Copyright Notice: | This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. FULL COPYRIGHT INFORMATION: | |
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| title | A general recurrent neural network approach to model genetic regulatory networks | |
| contributor.author | Xiao Hu | |
| contributor.author | Maglia, Anne | |
| contributor.author | Wunsch, Donald C. | |
| contributor.deptlab | Applied Computational Intelligence Laboratory | |
| contributor.deptlab | Biological Sciences | |
| contributor.deptlab | Electrical and Computer Engineering | |
| date.issued | 2005 | |
| date.submitted | 2007 | |
| publisher | Institute of Electrical and Electronics Engineers | |
| identifier.citation | Xiao Hu; Maglia, A.; Wunsch, D.C. "A General Recurrent Neural Network A pp.oach to Model Genetic Regulatory Networks" IEEE-EMBS 2005. 27th Annual International Conference of the Engineering in Medicine and Biology Society, 2005. 01-04 Sept. 2005 Pages: 4735- 4738 | |
| identifier.pub.URI | ||
| description.abstract | There is an urgent need for tools to unravel the complex interactions and functionalities of genes. As such, there has been much interest in reverse-engineering genetic regulatory networks from time series gene expression data. We use an artificial neural network to model the dynamics of complicated gene networks and to learn their parameters. The positive and negative regulations of genes are defined by a weight matrix, and different genes are allowed to have different decaying time constants. We demonstrate the effectiveness of the method by recreating the SOS DNA Repair network of Escherichia coli bacterium, previously discovered through experimental data. | |
| type | Article - Conference proceedings | |
| type.DCMIType | text | |
| type.status | Final version | |
| rights | This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. | |
| rights.URI | ||
| date.accessioned | 2007-04-05T14:26:38Z | |
| date.available | 2007-04-05T14:26:38Z | |
| identifier.persist.URI | ||
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