Prediction of protein-protein interactions from residue-pair interaction prediction
| Project/Area Number |
22500277
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Bioinformatics/Life informatics
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| Research Institution | 独立行政法人医薬基盤研究所 |
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Principal Investigator |
SHANDAR Ahmad 独立行政法人医薬基盤研究所, 創薬基盤研究部, 研究員 (80463298)
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| Project Period (FY) |
2010 – 2012
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| Project Status |
Completed (Fiscal Year 2012)
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| Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2012: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2011: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2010: ¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
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| Keywords | バイオインフォマティクス / Prediction / Binding sites / Protein interactions / Evolutionary profiles / Partner-aware prediction / Neural network / Transfer of training / Protein complex / Residue-pair / Protein-protein interaction / Binding site / Protein function / Amino acids / Protein structure / protein function |
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| Research Abstract |
Methods for prediction of protein-protein interaction sites, interacting partners and for defining similarity between protein-protein complexes for classification have been developed. Core method is based on a neural network ensemble. Accuracy of the model is significantly improved by real-time training of models over query-specific data sets. Improvement in prediction accuracy of a protein P due to the presence of a protein Q in the training data is used as pair-wise similarity metric. A faster version of the model is developed for genomic scale application.
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Report
(4 results)
Research Products
(25 results)
