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ファイル | 記述 | サイズ | フォーマット | |
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2014_382452.pdf | 1.44 MB | Adobe PDF | 見る/開く |
タイトル: | Network completion for static gene expression data. |
著者: | Nakajima, Natsu Akutsu, Tatsuya https://orcid.org/0000-0001-9763-797X (unconfirmed) |
著者名の別形: | 阿久津, 達也 |
発行日: | 26-Mar-2014 |
出版者: | Hindawi Publishing Corporation |
誌名: | Advances in bioinformatics |
巻: | 2014 |
論文番号: | 382452 |
抄録: | We tackle the problem of completing and inferring genetic networks under stationary conditions from static data, where network completion is to make the minimum amount of modifications to an initial network so that the completed network is most consistent with the expression data in which addition of edges and deletion of edges are basic modification operations. For this problem, we present a new method for network completion using dynamic programming and least-squares fitting. This method can find an optimal solution in polynomial time if the maximum indegree of the network is bounded by a constant. We evaluate the effectiveness of our method through computational experiments using synthetic data. Furthermore, we demonstrate that our proposed method can distinguish the differences between two types of genetic networks under stationary conditions from lung cancer and normal gene expression data. |
著作権等: | © 2014 Natsu Nakajima and Tatsuya Akutsu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
URI: | http://hdl.handle.net/2433/187362 |
DOI(出版社版): | 10.1155/2014/382452 |
PubMed ID: | 24826192 |
出現コレクション: | 学術雑誌掲載論文等 |
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