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Genetic algorithm solution for double digest problem
The strongly NP-Hard Double Digest Problem, for reconstructing the physical map of DNA sequence, in now using for efficient genotyping. Most of the existing methods are inefficient in tackling large instances due to the large search space for the problem which grows as a factorial function (a!)(b!)...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Biomedical Informatics
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3374354/ https://www.ncbi.nlm.nih.gov/pubmed/22715298 http://dx.doi.org/10.6026/97320630008453 |
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author | Ganjtabesh, Mohammad Ahrabian, H Nowzari-Dalini, A Kashani Moghadam, Z Razaghi |
author_facet | Ganjtabesh, Mohammad Ahrabian, H Nowzari-Dalini, A Kashani Moghadam, Z Razaghi |
author_sort | Ganjtabesh, Mohammad |
collection | PubMed |
description | The strongly NP-Hard Double Digest Problem, for reconstructing the physical map of DNA sequence, in now using for efficient genotyping. Most of the existing methods are inefficient in tackling large instances due to the large search space for the problem which grows as a factorial function (a!)(b!) of the numbers a and b of the DNA fragments generated by the two restriction enzymes. Also, none of the existing methods are able to handle the erroneous data. In this paper, we develop a novel method based on genetic algorithm for solving this problem and it is adapted to handle the erroneous data. Our genetic algorithm is implemented and compared with the other well-known existing algorithms. The obtained results show the efficiency (speedup) of our algorithm with respect to the other methods, specially for erroneous data. |
format | Online Article Text |
id | pubmed-3374354 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Biomedical Informatics |
record_format | MEDLINE/PubMed |
spelling | pubmed-33743542012-06-19 Genetic algorithm solution for double digest problem Ganjtabesh, Mohammad Ahrabian, H Nowzari-Dalini, A Kashani Moghadam, Z Razaghi Bioinformation Hypothesis The strongly NP-Hard Double Digest Problem, for reconstructing the physical map of DNA sequence, in now using for efficient genotyping. Most of the existing methods are inefficient in tackling large instances due to the large search space for the problem which grows as a factorial function (a!)(b!) of the numbers a and b of the DNA fragments generated by the two restriction enzymes. Also, none of the existing methods are able to handle the erroneous data. In this paper, we develop a novel method based on genetic algorithm for solving this problem and it is adapted to handle the erroneous data. Our genetic algorithm is implemented and compared with the other well-known existing algorithms. The obtained results show the efficiency (speedup) of our algorithm with respect to the other methods, specially for erroneous data. Biomedical Informatics 2012-05-31 /pmc/articles/PMC3374354/ /pubmed/22715298 http://dx.doi.org/10.6026/97320630008453 Text en © 2012 Biomedical Informatics This is an open-access article, which permits unrestricted use, distribution, and reproduction in any medium, for non-commercial purposes, provided the original author and source are credited. |
spellingShingle | Hypothesis Ganjtabesh, Mohammad Ahrabian, H Nowzari-Dalini, A Kashani Moghadam, Z Razaghi Genetic algorithm solution for double digest problem |
title | Genetic algorithm solution for double digest problem |
title_full | Genetic algorithm solution for double digest problem |
title_fullStr | Genetic algorithm solution for double digest problem |
title_full_unstemmed | Genetic algorithm solution for double digest problem |
title_short | Genetic algorithm solution for double digest problem |
title_sort | genetic algorithm solution for double digest problem |
topic | Hypothesis |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3374354/ https://www.ncbi.nlm.nih.gov/pubmed/22715298 http://dx.doi.org/10.6026/97320630008453 |
work_keys_str_mv | AT ganjtabeshmohammad geneticalgorithmsolutionfordoubledigestproblem AT ahrabianh geneticalgorithmsolutionfordoubledigestproblem AT nowzaridalinia geneticalgorithmsolutionfordoubledigestproblem AT kashanimoghadamzrazaghi geneticalgorithmsolutionfordoubledigestproblem |