| Budget Amount *help |
¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000)
Fiscal Year 2016: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2015: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2014: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
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| Outline of Final Research Achievements |
Based on regularization modeling and Markov chain Monte Carlo algorithms, we have developed methods for the protein complex prediction problem and the Bayes estimation of Gaussian distributions. Especially, for the protein complex prediction problem, we have empirically shown the effectiveness of a regularization term based on the information of mutually exclusive protein-protein interactions. In addition, we have developed a supervised learning algorithm for protein complexes with 2 or 3 components. Furthermore, we have designed a regularization term for controlling overlaps between predicted complexes, and showed that the new method with that regularization term outperforms others.
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