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タイトル: | Computing smallest intervention strategies for multiple metabolic networks in a boolean model. |
著者: | Lu, Wei Tamura, Takeyuki https://orcid.org/0000-0003-1596-901X (unconfirmed) Song, Jiangning Akutsu, Tatsuya https://orcid.org/0000-0001-9763-797X (unconfirmed) |
著者名の別形: | 田村, 武幸 |
発行日: | 15-Feb-2015 |
出版者: | Mary Ann Liebert Inc. |
誌名: | Journal of computational biology |
巻: | 22 |
号: | 2 |
開始ページ: | 85 |
終了ページ: | 110 |
抄録: | This article considers the problem whereby, given two metabolic networks N1 and N2, a set of source compounds, and a set of target compounds, we must find the minimum set of reactions whose removal (knockout) ensures that the target compounds are not producible in N1 but are producible in N2. Similar studies exist for the problem of finding the minimum knockout with the smallest side effect for a single network. However, if technologies of external perturbations are advanced in the near future, it may be important to develop methods of computing the minimum knockout for multiple networks (MKMN). Flux balance analysis (FBA) is efficient if a well-polished model is available. However, that is not always the case. Therefore, in this article, we study MKMN in Boolean models and an elementary mode (EM)-based model. Integer linear programming (ILP)-based methods are developed for these models, since MKMN is NP-complete for both the Boolean model and the EM-based model. Computer experiments are conducted with metabolic networks of clostridium perfringens SM101 and bifidobacterium longum DJO10A, respectively known as bad bacteria and good bacteria for the human intestine. The results show that larger networks are more likely to have MKMN solutions. However, solving for these larger networks takes a very long time, and often the computation cannot be completed. This is reasonable, because small networks do not have many alternative pathways, making it difficult to satisfy the MKMN condition, whereas in large networks the number of candidate solutions explodes. Our developed software minFvskO is available online. |
著作権等: | Final publication is available from Mary Ann Liebert, Inc., publishers http://dx.doi.org/10.1089/cmb.2014.0274. The full-text file will be made open to the public on 16 February 2016 in accordance with publisher's 'Terms and Conditions for Self-Archiving'. この論文は出版社版でありません。引用の際には出版社版をご確認ご利用ください。 This is not the published version. Please cite only the published version. |
URI: | http://hdl.handle.net/2433/200202 |
DOI(出版社版): | 10.1089/cmb.2014.0274 |
PubMed ID: | 25684199 |
出現コレクション: | 学術雑誌掲載論文等 |
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