2016 Fiscal Year Final Research Report
Fast Similarity Search on Big Data based on SMAD and its applications
| Project/Area Number |
25280002
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Partial Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Theory of informatics
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| Research Institution | The University of Tokyo |
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Principal Investigator |
Shibuya Tetsuo 東京大学, 医科学研究所, 准教授 (60396893)
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| Project Period (FY) |
2013-04-01 – 2017-03-31
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| Keywords | アルゴリズム / ビッグデータ / 検索 / タンパク質立体構造 / 次世代シークエンサー |
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| Outline of Final Research Achievements |
We aimed to develop very fast indexing and searching algorithms for big-data databases, especially the protein 3-D structure databases, and also aimed to develop application algorithms utilizing them. We succeeded in developing dramatically faster protein function prediction algorithms without any loss of accuracy. We also succeeded in developing faster algorithms for protein 3-D structure searching for wider applications. We also developed several analysis algorithms for next-generation sequencer data.
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| Free Research Field |
バイオインフォマティクス
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