Restarting and recentering genetic algorithm variations for DNA fragment assembly: The necessity of a multi-strategy approach
DNA Fragment assembly – an NP-Hard problem – is one of the major steps in of DNA sequencing. Multiple strategies have been used for this problem, including greedy graph-based algorithms, deBruijn graphs, and the overlap-layout-consensus approach. This study focuses on the overlap-layout-consensus ap...
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| Vydáno v: | BioSystems Ročník 150; s. 35 - 45 |
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01.12.2016
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| ISSN: | 0303-2647, 1872-8324 |
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| Abstract | DNA Fragment assembly – an NP-Hard problem – is one of the major steps in of DNA sequencing. Multiple strategies have been used for this problem, including greedy graph-based algorithms, deBruijn graphs, and the overlap-layout-consensus approach.
This study focuses on the overlap-layout-consensus approach. Heuristics and computational intelligence methods are combined to exploit their respective benefits. These algorithm combinations were able to produce high quality results surpassing the best results obtained by a number of competitive algorithms specially designed and tuned for this problem on thirteen of sixteen popular benchmarks.
This work also reinforces the necessity of using multiple search strategies as it is clearly observed that algorithm performance is dependent on problem instance; without a deeper look into many searches, top solutions could be missed entirely. |
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| AbstractList | DNA Fragment assembly – an NP-Hard problem – is one of the major steps in of DNA sequencing. Multiple strategies have been used for this problem, including greedy graph-based algorithms, deBruijn graphs, and the overlap-layout-consensus approach.
This study focuses on the overlap-layout-consensus approach. Heuristics and computational intelligence methods are combined to exploit their respective benefits. These algorithm combinations were able to produce high quality results surpassing the best results obtained by a number of competitive algorithms specially designed and tuned for this problem on thirteen of sixteen popular benchmarks.
This work also reinforces the necessity of using multiple search strategies as it is clearly observed that algorithm performance is dependent on problem instance; without a deeper look into many searches, top solutions could be missed entirely. DNA Fragment assembly - an NP-Hard problem - is one of the major steps in of DNA sequencing. Multiple strategies have been used for this problem, including greedy graph-based algorithms, deBruijn graphs, and the overlap-layout-consensus approach. This study focuses on the overlap-layout-consensus approach. Heuristics and computational intelligence methods are combined to exploit their respective benefits. These algorithm combinations were able to produce high quality results surpassing the best results obtained by a number of competitive algorithms specially designed and tuned for this problem on thirteen of sixteen popular benchmarks. This work also reinforces the necessity of using multiple search strategies as it is clearly observed that algorithm performance is dependent on problem instance; without a deeper look into many searches, top solutions could be missed entirely. |
| Author | Houghten, Sheridan Hughes, James Alexander Ashlock, Daniel |
| Author_xml | – sequence: 1 givenname: James Alexander surname: Hughes fullname: Hughes, James Alexander email: jh08tt@gmail.ca organization: Computer Science Department, Brock University, 500 Glenridge Ave., St. Catharines, Ontario L2S 3A1, Canada – sequence: 2 givenname: Sheridan surname: Houghten fullname: Houghten, Sheridan organization: Computer Science Department, Brock University, 500 Glenridge Ave., St. Catharines, Ontario L2S 3A1, Canada – sequence: 3 givenname: Daniel surname: Ashlock fullname: Ashlock, Daniel organization: Department of Mathematics and Statistics, University of Guelph, 50 Stone Rd. E, Guelph, Ontario N1G 2W1, Canada |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/27521768$$D View this record in MEDLINE/PubMed |
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| CitedBy_id | crossref_primary_10_1111_itor_13164 crossref_primary_10_1016_j_ins_2019_10_026 crossref_primary_10_1016_j_eswa_2018_02_018 crossref_primary_10_1016_j_ins_2017_07_039 crossref_primary_10_1016_j_asoc_2020_106256 crossref_primary_10_1109_ACCESS_2020_3044857 |
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| Keywords | Representation DNA fragment assembly problem Island Model Evolutionary algorithm Recentering-restarting Ring Species |
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| SubjectTerms | Algorithms Animals Artificial Intelligence DNA - genetics DNA fragment assembly problem DNA Fragmentation Evolutionary algorithm Humans Island Model Recentering-restarting Representation Ring Species Sequence Analysis, DNA - methods |
| Title | Restarting and recentering genetic algorithm variations for DNA fragment assembly: The necessity of a multi-strategy approach |
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