A non-dominated sorting differential search algorithm flux balance analysis (ndsDSAFBA) for in silico multiobjective optimization in identifying reactions knockout
Metabolic engineering is defined as improving the cellular activities of an organism by manipulating the metabolic, signal or regulatory network. In silico reaction knockout simulation is one of the techniques applied to analyse the effects of genetic perturbations on metabolite production. Many met...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier Ltd
2019
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| Online Access: | http://eprints.utm.my/89410/1/KautharMohdDaud2019_ANonDominatedSortingDifferentialSearchAlgorithm.pdf |
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| author | Mohd. Daud, Kauthar Mohamad, Mohd. Saberi Zakaria, Zalmiyah Hassan, Rohayanti Shah, Zuraini Ali Deris, Safaai Ibrahim, Zuwairie Napis, Suhaimi Sinnott, Richard O. |
| author_facet | Mohd. Daud, Kauthar Mohamad, Mohd. Saberi Zakaria, Zalmiyah Hassan, Rohayanti Shah, Zuraini Ali Deris, Safaai Ibrahim, Zuwairie Napis, Suhaimi Sinnott, Richard O. |
| author_sort | Mohd. Daud, Kauthar |
| collection | ePrints |
| description | Metabolic engineering is defined as improving the cellular activities of an organism by manipulating the metabolic, signal or regulatory network. In silico reaction knockout simulation is one of the techniques applied to analyse the effects of genetic perturbations on metabolite production. Many methods consider growth coupling as the objective function, whereby it searches for mutants that maximise the growth and production rate. However, the final goal is to increase the production rate. Furthermore, they produce one single solution, though in reality, cells do not focus on one objective and they need to consider various different competing objectives. In this work, a method, termed ndsDSAFBA (non-dominated sorting Differential Search Algorithm and Flux Balance Analysis), has been developed to find the reaction knockouts involved in maximising the production rate and growth rate of the mutant, by incorporating Pareto dominance concepts. The proposed ndsDSAFBA method was validated using three genome-scale metabolic models. We obtained a set of non-dominated solutions, with each solution representing a different mutant strain. The results obtained were compared with the single objective optimisation (SOO) and multi-objective optimisation (MOO) methods. The results demonstrate that ndsDSAFBA is better than the other methods in terms of production rate and growth rate. |
| first_indexed | 2024-03-05T20:47:37Z |
| format | Article |
| id | utm.eprints-89410 |
| institution | Universiti Teknologi Malaysia - ePrints |
| language | English |
| last_indexed | 2024-03-05T20:47:37Z |
| publishDate | 2019 |
| publisher | Elsevier Ltd |
| record_format | dspace |
| spelling | utm.eprints-894102021-02-22T06:04:37Z http://eprints.utm.my/89410/ A non-dominated sorting differential search algorithm flux balance analysis (ndsDSAFBA) for in silico multiobjective optimization in identifying reactions knockout Mohd. Daud, Kauthar Mohamad, Mohd. Saberi Zakaria, Zalmiyah Hassan, Rohayanti Shah, Zuraini Ali Deris, Safaai Ibrahim, Zuwairie Napis, Suhaimi Sinnott, Richard O. QA75 Electronic computers. Computer science Metabolic engineering is defined as improving the cellular activities of an organism by manipulating the metabolic, signal or regulatory network. In silico reaction knockout simulation is one of the techniques applied to analyse the effects of genetic perturbations on metabolite production. Many methods consider growth coupling as the objective function, whereby it searches for mutants that maximise the growth and production rate. However, the final goal is to increase the production rate. Furthermore, they produce one single solution, though in reality, cells do not focus on one objective and they need to consider various different competing objectives. In this work, a method, termed ndsDSAFBA (non-dominated sorting Differential Search Algorithm and Flux Balance Analysis), has been developed to find the reaction knockouts involved in maximising the production rate and growth rate of the mutant, by incorporating Pareto dominance concepts. The proposed ndsDSAFBA method was validated using three genome-scale metabolic models. We obtained a set of non-dominated solutions, with each solution representing a different mutant strain. The results obtained were compared with the single objective optimisation (SOO) and multi-objective optimisation (MOO) methods. The results demonstrate that ndsDSAFBA is better than the other methods in terms of production rate and growth rate. Elsevier Ltd 2019-10 Article PeerReviewed application/pdf en http://eprints.utm.my/89410/1/KautharMohdDaud2019_ANonDominatedSortingDifferentialSearchAlgorithm.pdf Mohd. Daud, Kauthar and Mohamad, Mohd. Saberi and Zakaria, Zalmiyah and Hassan, Rohayanti and Shah, Zuraini Ali and Deris, Safaai and Ibrahim, Zuwairie and Napis, Suhaimi and Sinnott, Richard O. (2019) A non-dominated sorting differential search algorithm flux balance analysis (ndsDSAFBA) for in silico multiobjective optimization in identifying reactions knockout. Computers in Biology and Medicine, 113 . pp. 1-13. ISSN 0010-4825 http://dx.doi.org/10.1016/j.compbiomed.2019.103390 DOI:10.1016/j.compbiomed.2019.103390 |
| spellingShingle | QA75 Electronic computers. Computer science Mohd. Daud, Kauthar Mohamad, Mohd. Saberi Zakaria, Zalmiyah Hassan, Rohayanti Shah, Zuraini Ali Deris, Safaai Ibrahim, Zuwairie Napis, Suhaimi Sinnott, Richard O. A non-dominated sorting differential search algorithm flux balance analysis (ndsDSAFBA) for in silico multiobjective optimization in identifying reactions knockout |
| title | A non-dominated sorting differential search algorithm flux balance analysis (ndsDSAFBA) for in silico multiobjective optimization in identifying reactions knockout |
| title_full | A non-dominated sorting differential search algorithm flux balance analysis (ndsDSAFBA) for in silico multiobjective optimization in identifying reactions knockout |
| title_fullStr | A non-dominated sorting differential search algorithm flux balance analysis (ndsDSAFBA) for in silico multiobjective optimization in identifying reactions knockout |
| title_full_unstemmed | A non-dominated sorting differential search algorithm flux balance analysis (ndsDSAFBA) for in silico multiobjective optimization in identifying reactions knockout |
| title_short | A non-dominated sorting differential search algorithm flux balance analysis (ndsDSAFBA) for in silico multiobjective optimization in identifying reactions knockout |
| title_sort | non dominated sorting differential search algorithm flux balance analysis ndsdsafba for in silico multiobjective optimization in identifying reactions knockout |
| topic | QA75 Electronic computers. Computer science |
| url | http://eprints.utm.my/89410/1/KautharMohdDaud2019_ANonDominatedSortingDifferentialSearchAlgorithm.pdf |
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