2013 Fiscal Year Final Research Report
The Closest-Neighbor Trimming Algorithm for Resampling Genetic Sequence Datasets
| Project/Area Number |
24700289
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Bioinformatics/Life informatics
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| Research Institution | Nagahama Institute of Bio-Science and Technology |
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Principal Investigator |
YONEZAWA Kouki 長浜バイオ大学, バイオサイエンス学部, 助手 (00374744)
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| Project Period (FY) |
2012-04-01 – 2014-03-31
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| Keywords | バイオインフォマティクス / 人獣共通感染症 / リサンプリング / 分子系統樹 |
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| Research Abstract |
A large number of nucleotide sequences of various pathogens are available in public databases. The growth of the datasets has resulted in an enormous increase in computational costs. Moreover, due to differences in surveillance activities, the number of sequences found in databases varies from one country to another and from year to year. Therefore it is important to study resampling methods to reduce the sampling bias. A novel algorithm| called the closest-neighbor trimming method|that resamples a given number of sequences from a large nucleotide sequence dataset was proposed. The performance of the proposed algorithm was compared with other algorithms by using the nucleotide sequences of human H3N2 influenza viruses. Since nucleotide sequences are among the most widely used materials for life sciences, we anticipate that our algorithm to various datasets will result in reducing sampling bias.
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