An Efficient Genome Fragment Assembling Using GA with Neighborhood Aware Fitness Function
To decode a long genome sequence, shotgun sequencing is the state-of-the-art technique. It needs to properly sequence a very large number, sometimes as large as millions, of short partially readable strings (fragments). Arranging those fragments in correct sequence is known as fragment assembling, w...
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| Format: | Article |
| Language: | English |
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Wiley
2012-01-01
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| Series: | Applied Computational Intelligence and Soft Computing |
| Online Access: | http://dx.doi.org/10.1155/2012/945401 |
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| author | Satoko Kikuchi Goutam Chakraborty |
| author_facet | Satoko Kikuchi Goutam Chakraborty |
| author_sort | Satoko Kikuchi |
| collection | DOAJ |
| description | To decode a long genome sequence, shotgun sequencing is the state-of-the-art technique. It needs to properly sequence a very large number, sometimes as large as millions, of short partially readable strings (fragments). Arranging those fragments in correct sequence is known as fragment assembling, which is an NP-problem. Presently used methods require enormous computational cost. In this work, we have shown how our modified genetic algorithm (GA) could solve this problem efficiently. In the proposed GA, the length of the chromosome, which represents the volume of the search space, is reduced with advancing generations, and thereby improves search efficiency. We also introduced a greedy mutation, by swapping nearby fragments using some heuristics, to improve the fitness of chromosomes. We compared results with Parsons’ algorithm which is based on GA too. We used fragments with partial reads on both sides, mimicking fragments in real genome assembling process. In Parsons’ work base-pair array of the whole fragment is known. Even then, we could obtain much better results, and we succeeded in restructuring contigs covering 100% of the genome sequences. |
| format | Article |
| id | doaj-art-20973baaf895492894812e609b3dece3 |
| institution | Kabale University |
| issn | 1687-9724 1687-9732 |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Applied Computational Intelligence and Soft Computing |
| spelling | doaj-art-20973baaf895492894812e609b3dece32025-02-03T05:50:51ZengWileyApplied Computational Intelligence and Soft Computing1687-97241687-97322012-01-01201210.1155/2012/945401945401An Efficient Genome Fragment Assembling Using GA with Neighborhood Aware Fitness FunctionSatoko Kikuchi0Goutam Chakraborty1Faculty of Software and Information Science, Iwate Prefectural University, Takizawa-mura, Iwate 020-0193, JapanFaculty of Software and Information Science, Iwate Prefectural University, Takizawa-mura, Iwate 020-0193, JapanTo decode a long genome sequence, shotgun sequencing is the state-of-the-art technique. It needs to properly sequence a very large number, sometimes as large as millions, of short partially readable strings (fragments). Arranging those fragments in correct sequence is known as fragment assembling, which is an NP-problem. Presently used methods require enormous computational cost. In this work, we have shown how our modified genetic algorithm (GA) could solve this problem efficiently. In the proposed GA, the length of the chromosome, which represents the volume of the search space, is reduced with advancing generations, and thereby improves search efficiency. We also introduced a greedy mutation, by swapping nearby fragments using some heuristics, to improve the fitness of chromosomes. We compared results with Parsons’ algorithm which is based on GA too. We used fragments with partial reads on both sides, mimicking fragments in real genome assembling process. In Parsons’ work base-pair array of the whole fragment is known. Even then, we could obtain much better results, and we succeeded in restructuring contigs covering 100% of the genome sequences.http://dx.doi.org/10.1155/2012/945401 |
| spellingShingle | Satoko Kikuchi Goutam Chakraborty An Efficient Genome Fragment Assembling Using GA with Neighborhood Aware Fitness Function Applied Computational Intelligence and Soft Computing |
| title | An Efficient Genome Fragment Assembling Using GA with Neighborhood Aware Fitness Function |
| title_full | An Efficient Genome Fragment Assembling Using GA with Neighborhood Aware Fitness Function |
| title_fullStr | An Efficient Genome Fragment Assembling Using GA with Neighborhood Aware Fitness Function |
| title_full_unstemmed | An Efficient Genome Fragment Assembling Using GA with Neighborhood Aware Fitness Function |
| title_short | An Efficient Genome Fragment Assembling Using GA with Neighborhood Aware Fitness Function |
| title_sort | efficient genome fragment assembling using ga with neighborhood aware fitness function |
| url | http://dx.doi.org/10.1155/2012/945401 |
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