| Presentation | 2006-06-15 Building a New Mutation Model based on Bayesian Networks and estimation by a modified Belief Propagation algorithm Yoshinori DOI, Noboru MURATA, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | It is thought that ancient DNA repair proteins were more active than present ones, and obtaining the ancient DNA repair proteins would be helpful for hereditary diseases such as cancer. We propose a mutation model using Bayesian Networks and a modified the belief propagation algorithm, which is applied to estimate an ancient protein from multiple proteins that are present. Also, we applied the cross-validation to derive an optimum parameter. We virtually generated multiple proteins from an ancient protein following a specific mutation probability, and evaluated our model by estimating the ancient protein by the proposed model. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Bayesian Networks / Bayes estimation / Belief Propagation / Mutation model |
| Paper # | NC2006-20 |
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| Committee | NC |
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| Conference Date | 2006/6/8(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Neurocomputing (NC) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Building a New Mutation Model based on Bayesian Networks and estimation by a modified Belief Propagation algorithm |
| Sub Title (in English) | |
| Keyword(1) | Bayesian Networks |
| Keyword(2) | Bayes estimation |
| Keyword(3) | Belief Propagation |
| Keyword(4) | Mutation model |
| 1st Author's Name | Yoshinori DOI |
| 1st Author's Affiliation | Waseda University() |
| 2nd Author's Name | Noboru MURATA |
| 2nd Author's Affiliation | Waseda University |
| Date | 2006-06-15 |
| Paper # | NC2006-20 |
| Volume (vol) | vol.106 |
| Number (no) | 101 |
| Page | pp.pp.- |
| #Pages | 6 |
| Date of Issue | |