"Integer Programming-Based Method For Designing Synthetic Metabolic Networks By Minimum Reaction Insertion In A Boolean Model." - Information and Links:

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"Integer Programming-Based Method For Designing Synthetic Metabolic Networks By Minimum Reaction Insertion In A Boolean Model." and the language of the book is English.


“Integer Programming-Based Method For Designing Synthetic Metabolic Networks By Minimum Reaction Insertion In A Boolean Model.” Metadata:

  • Title: ➤  Integer Programming-Based Method For Designing Synthetic Metabolic Networks By Minimum Reaction Insertion In A Boolean Model.
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  • Language: English

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  • Internet Archive ID: pubmed-PMC3961429

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This article is from <a href="//archive.org/search.php?query=journaltitle%3A%28PLoS%20ONE%29" rel="nofollow">PLoS ONE</a>, <a href="//archive.org/search.php?query=journaltitle%3A%28PLoS%20ONE%29%20AND%20volume%3A%289%29" rel="nofollow">volume 9</a>.<h2>Abstract</h2>In this paper, we consider the Minimum Reaction Insertion (MRI) problem for finding the minimum number of additional reactions from a reference metabolic network to a host metabolic network so that a target compound becomes producible in the revised host metabolic network in a Boolean model. Although a similar problem for larger networks is solvable in a flux balance analysis (FBA)-based model, the solution of the FBA-based model tends to include more reactions than that of the Boolean model. However, solving MRI using the Boolean model is computationally more expensive than using the FBA-based model since the Boolean model needs more integer variables. Therefore, in this study, to solve MRI for larger networks in the Boolean model, we have developed an efficient Integer Programming formalization method in which the number of integer variables is reduced by the notion of feedback vertex set and minimal valid assignment. As a result of computer experiments conducted using the data of metabolic networks of E. coli and reference networks downloaded from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, we have found that the developed method can appropriately solve MRI in the Boolean model and is applicable to large scale-networks for which an exhaustive search does not work. We have also compared the developed method with the existing connectivity-based methods and FBA-based methods, and show the difference between the solutions of our method and the existing methods. A theoretical analysis of MRI is also conducted, and the NP-completeness of MRI is proved in the Boolean model. Our developed software is available at “http://sunflower.kuicr.kyoto-u.ac.jp/~rogi/minRect/minRect.html.”

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