Abstract
Codon usage bias is the preferential use of synonymous codons. First models that studied this phenomenon assumed that the population is at mutation-selection-drift equilibrium, but more advanced models were proposed later to incorporate demographic changes. One of these models proposed by Zeng and Charlesworth represents the evolutionary process by a Markov model, allowing for changes in the population size. Their model is, however, too simple to reflect many realistic demographic changes. In this paper, we extend their model by allowing complex demographies with many changes in population size. Such extension requires a more powerful optimization algorithm compared with the simple one used in the model proposed by Zeng and Charlesworth. The optimization algorithm we use is a version of the genetic algorithm that we develop particularly for this purpose. We validate our method using simulated data.
Original language | English |
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Title of host publication | 2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 2566-2573 |
Number of pages | 8 |
ISBN (Electronic) | 9781509046010 |
DOIs | |
Publication status | Published - 5 Jul 2017 |
Externally published | Yes |
Event | 2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Donostia-San Sebastian, Spain Duration: 5 Jun 2017 → 8 Jun 2017 |
Publication series
Name | 2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Proceedings |
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Conference
Conference | 2017 IEEE Congress on Evolutionary Computation, CEC 2017 |
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Country/Territory | Spain |
City | Donostia-San Sebastian |
Period | 5/06/17 → 8/06/17 |
Keywords
- Codon usage bias
- Genetic algorithms
- Modeling
- Optimization
- Population genetics
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Networks and Communications
- Computer Science Applications
- Signal Processing
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Marwan Fuad
- School of Computing, Mathematics and Data Sciences - Assistant Professor Academic
Person: Teaching and Research