RNA-protein interaction prediction based on machine learning and optimization
| Project/Area Number |
23650153
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| Research Category |
Grant-in-Aid for Challenging Exploratory Research
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| Allocation Type | Multi-year Fund |
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| Research Field |
Bioinformatics/Life informatics
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| Research Institution | Nara Institute of Science and Technology |
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Principal Investigator |
SEKI Hiroyuki 奈良先端科学技術大学院大学, 情報科学研究科, 教授 (80196948)
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| Co-Investigator(Kenkyū-buntansha) |
KATO Yuki 奈良先端科学技術大学院大学, 情報科学研究科, 助教 (10511280)
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| Project Period (FY) |
2011 – 2012
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| Project Status |
Completed (Fiscal Year 2012)
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| Budget Amount *help |
¥3,640,000 (Direct Cost: ¥2,800,000、Indirect Cost: ¥840,000)
Fiscal Year 2012: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2011: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
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| Keywords | バイオインフォマティクス / RNA-タンパク質相互作用 / RNA2次構造 / RNA間相互作用 / RNA構造アラインメント / 機械学習 / 最適化 / RNA２次構造 |
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| Research Abstract |
From a viewpoint of RNA sequenceanalysis, we first developed a mathematical method for predicting complex folding structures of an RNA when its single sequence is given. We then developed a computational method for aligning and folding multiple RNA sequences simultaneously. All of these methods were validated on real biological data, achieving fast run-time and goodprediction accuracy at least comparable to those of earlier methods. The proposed technologies are expected to provide a good practical foundation for RNA-protein interaction prediction.
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Report
(3 results)
Research Products
(40 results)
