NDLI: Measuring Structural Robustness of Metabolic Networks under a Boolean Model Using Integer Programming and Feedback Vertex Sets

Content Provider	IEEE Xplore Digital Library
Author	Tamura, T. Takemoto, K. Akutsu, T.
Copyright Year	2009
Abstract	Robustness is one of the important features of living organisms. For example, many organisms have strong adaptability to environmental changes and many organisms can live even if some of their genes are mutated. Besides, it is considered that cancer cells are very robust and thus cancers are difficult to treat. Therefore, it is important to identify origins of robustness in various kinds of organisms.Though several methods have been proposed for measuring robustness in metabolic networks or signal transduction networks, most methods require large computation time or are not guaranteed to output optimal solutions.In this paper, we formalized the problem as an integer program, where an objective function is to minimize the number of reactions to be inactivated so that at least one of the target compounds cannot be synthesized.In order to cope with cycles and reversible reactions, we developed a novel integer programming formalization method using a feedback vertex set (FVS).When applied to an E. coli metabolic network consisting of Glycolysis/Glyconeogenesis, Citrate cycle and Pentose phosphate pathway obtained from KEGG database, we could find an optimal set of enzymes to be inactivated several times faster than a naive method.
Starting Page	819
Ending Page	824
File Size	273413
Page Count	6
File Format	PDF
ISBN	9781424435692
DOI	10.1109/CISIS.2009.49
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-03-16
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Boolean model. integer programming robustness Linear programming Biochemistry Organisms Time measurement Feedback Signal processing Robustness Computer networks Network synthesis Cancer metabolic network
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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