Heuristic-Based Ant Colony Optimization Algorithm For Protein Functional Module Detection In Protein Interaction Network
Ant colony optimization (ACO) is a metaheuristic algorithm that has been successfully applied to several types of optimization problems such as scheduling, routing, and more recently for solving protein functional module detection (PFMD) problem in protein-protein interaction (PPI) networks. For a s...
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| Format: | Thesis |
| Language: | English |
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2017
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| Online Access: | http://eprints.usm.my/42907/1/JAMALUDIN__SALLIM.pdf |
| _version_ | 1797010921548152832 |
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| author | SALLIM, JAMALUDIN |
| author_facet | SALLIM, JAMALUDIN |
| author_sort | SALLIM, JAMALUDIN |
| collection | USM |
| description | Ant colony optimization (ACO) is a metaheuristic algorithm that has been successfully applied to several types of optimization problems such as scheduling, routing, and more recently for solving protein functional module detection (PFMD) problem in protein-protein interaction (PPI) networks. For a small PPI data size, ACO has been successfully applied to but it is not suitable for large and noisy PPI data, which has caused to premature convergence and stagnation in the searching process. To cope with the aforementioned limitations, we propose two new enhancements of ACO to solve PFMD problem. |
| first_indexed | 2024-03-06T15:26:43Z |
| format | Thesis |
| id | usm.eprints-42907 |
| institution | Universiti Sains Malaysia |
| language | English |
| last_indexed | 2024-03-06T15:26:43Z |
| publishDate | 2017 |
| record_format | dspace |
| spelling | usm.eprints-429072019-04-12T05:24:59Z http://eprints.usm.my/42907/ Heuristic-Based Ant Colony Optimization Algorithm For Protein Functional Module Detection In Protein Interaction Network SALLIM, JAMALUDIN QA75.5-76.95 Electronic computers. Computer science Ant colony optimization (ACO) is a metaheuristic algorithm that has been successfully applied to several types of optimization problems such as scheduling, routing, and more recently for solving protein functional module detection (PFMD) problem in protein-protein interaction (PPI) networks. For a small PPI data size, ACO has been successfully applied to but it is not suitable for large and noisy PPI data, which has caused to premature convergence and stagnation in the searching process. To cope with the aforementioned limitations, we propose two new enhancements of ACO to solve PFMD problem. 2017-07 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/42907/1/JAMALUDIN__SALLIM.pdf SALLIM, JAMALUDIN (2017) Heuristic-Based Ant Colony Optimization Algorithm For Protein Functional Module Detection In Protein Interaction Network. PhD thesis, Universiti Sains Malaysia. |
| spellingShingle | QA75.5-76.95 Electronic computers. Computer science SALLIM, JAMALUDIN Heuristic-Based Ant Colony Optimization Algorithm For Protein Functional Module Detection In Protein Interaction Network |
| title | Heuristic-Based Ant Colony Optimization Algorithm For Protein Functional Module Detection In Protein Interaction Network |
| title_full | Heuristic-Based Ant Colony Optimization Algorithm For Protein Functional Module Detection In Protein Interaction Network |
| title_fullStr | Heuristic-Based Ant Colony Optimization Algorithm For Protein Functional Module Detection In Protein Interaction Network |
| title_full_unstemmed | Heuristic-Based Ant Colony Optimization Algorithm For Protein Functional Module Detection In Protein Interaction Network |
| title_short | Heuristic-Based Ant Colony Optimization Algorithm For Protein Functional Module Detection In Protein Interaction Network |
| title_sort | heuristic based ant colony optimization algorithm for protein functional module detection in protein interaction network |
| topic | QA75.5-76.95 Electronic computers. Computer science |
| url | http://eprints.usm.my/42907/1/JAMALUDIN__SALLIM.pdf |
| work_keys_str_mv | AT sallimjamaludin heuristicbasedantcolonyoptimizationalgorithmforproteinfunctionalmoduledetectioninproteininteractionnetwork |