- Title
- mDBN: motif based learning of gene regulatory networks using dynamic Bayesian networks
- Creator
- Morshed, Nizamul; Chetty, Madhu; Nguyen, Vinh; Caelli, Terry
- Date
- 2013
- Type
- Text; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/74339
- Identifier
- vital:7248
- Identifier
- ISBN:9781450319638
- Identifier
-
https://doi.org/10.1145/2463372.2463406
- Abstract
- Solutions for deriving the most consistent Bayesian gene regulatory network model from given data sets using evolutionary algorithms typically only result in locally optimal solutions.
- Publisher
- Association for Computing Machinery Inc. (ACM)
- Relation
- Proceedings of the Genetic and Evolutionary Computation Conference, GECCO'13, Association for Computing Machinery Inc. (ACM), 2013 p. 279-286
- Rights
- This metadata is freely available under a CCO license
- Subject
- 0801 Artificial Intelligence and Image Processing; Dynamic bayesian network; Gene regulatory network; Genetic algorithm; Motif
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