Presentation | 2005-01-27 A basic study of genetic network estimation with Bayesian network Kimi SO, Takeo OKAZAKI, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | The Bayesian network is a probability network which builds a network from the dependency of causal relationship and correlation between variables. It consists of DAG and conditional probability. On the other hand, in the field of bioinformatics, an analysis of genetic network is one of the research projects. A gene affects other genes. The conditional probability model which made each gene the variable can express this relation. In this paper, we propose the procedure of genetic network estimation with Bayesian network. It is known that the gene expression data used for analysis of a genetic network has large-scale noise. Then, this procedure can consider other information besides gene expression data as constraint. We also conducted the evaluation experiment for verifying whether suitable graph can be chosen with the procedure. So, the result of this experiment is also reported collectively. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Bayesian network / genetic network / matrix representation / DAG / gene expression data |
Paper # | CST2004-43 |
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Committee | CST |
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Conference Date | 2005/1/20(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Concurrent System Technology (CST) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | A basic study of genetic network estimation with Bayesian network |
Sub Title (in English) | |
Keyword(1) | Bayesian network |
Keyword(2) | genetic network |
Keyword(3) | matrix representation |
Keyword(4) | DAG |
Keyword(5) | gene expression data |
1st Author's Name | Kimi SO |
1st Author's Affiliation | Graduate School of Science and Engineering, University of the Ryukyus() |
2nd Author's Name | Takeo OKAZAKI |
2nd Author's Affiliation | Faculty of Engineering, University of the Ryukyus |
Date | 2005-01-27 |
Paper # | CST2004-43 |
Volume (vol) | vol.104 |
Number (no) | 593 |
Page | pp.pp.- |
#Pages | 5 |
Date of Issue |