Computing Smallest Intervention Strategies for Multiple Metabolic Networks in a Boolean Model
文献类型：期刊论文
| 作者 | Lu, Wei1; Tamura, Takeyuki1; Song, Jiangning2,3; Akutsu, Tatsuya1 |
| 刊名 | JOURNAL OF COMPUTATIONAL BIOLOGY
 |
| 出版日期 | 2015-02-01 |
| 卷号 | 22期号:2页码:85-110 |
| 关键词 | metabolic network Boolean model NP-complete elementary mode integer linear programming algorithm |
| 英文摘要 | This article considers the problem whereby, given two metabolic networks N-1 and N-2, 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 N-1 but are producible in N-2. 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. |
| WOS标题词 | Science & Technology ; Life Sciences & Biomedicine ; Technology ; Physical Sciences |
| 类目[WOS] | Biochemical Research Methods ; Biotechnology & Applied Microbiology ; Computer Science, Interdisciplinary Applications ; Mathematical & Computational Biology ; Statistics & Probability |
| 研究领域[WOS] | Biochemistry & Molecular Biology ; Biotechnology & Applied Microbiology ; Computer Science ; Mathematical & Computational Biology ; Mathematics |
| 关键词[WOS] | MINIMAL CUT SETS ; FLUX BALANCE ANALYSIS ; KNOCKOUT STRATEGIES ; CONSTRUCTION ; DEFINITION ; ROBUSTNESS ; ALGORITHMS ; EVOLUTION ; PATHWAYS ; FAILURE |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000349322900002 |
| 源URL | [http://124.16.173.210/handle/834782/1425]  |
| 专题 | 天津工业生物技术研究所_结构生物信息学和整合系统生物学实验室 宋江宁_期刊论文 |
| 作者单位 | 1.Kyoto Univ, Inst Chem Res, Bioinformat Ctr, Uji, Kyoto 6110011, Japan 2.Monash Univ, Dept Biochem & Mol Biol, Melbourne, Vic 3004, Australia 3.Chinese Acad Sci, Natl Engn Lab Ind Enzymes, Tianjin Inst Ind Biotechnol, Tianjin, Peoples R China |
| 推荐引用方式 GB/T 7714 | Lu, Wei,Tamura, Takeyuki,Song, Jiangning,et al. Computing Smallest Intervention Strategies for Multiple Metabolic Networks in a Boolean Model[J]. JOURNAL OF COMPUTATIONAL BIOLOGY,2015,22(2):85-110. |
| APA | Lu, Wei,Tamura, Takeyuki,Song, Jiangning,&Akutsu, Tatsuya.(2015).Computing Smallest Intervention Strategies for Multiple Metabolic Networks in a Boolean Model.JOURNAL OF COMPUTATIONAL BIOLOGY,22(2),85-110. |
| MLA | Lu, Wei,et al."Computing Smallest Intervention Strategies for Multiple Metabolic Networks in a Boolean Model".JOURNAL OF COMPUTATIONAL BIOLOGY 22.2(2015):85-110. |
入库方式： OAI收割
来源：天津工业生物技术研究所
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