NDLI: Manipulating the Steady State of Metabolic Pathways

Content Provider	ACM Digital Library
Author	Song, Bin Kahveci, Tamer Buyuktahtakin, I. Esra Ranka, Sanjay
Abstract	Metabolic pathways show the complex interactions among enzymes that transform chemical compounds. The state of a metabolic pathway can be expressed as a vector, which denotes the yield of the compounds or the flux in that pathway at a given time. The steady state is a state that remains unchanged over time. Altering the state of the metabolism is very important for many applications such as biomedicine, biofuels, food industry, and cosmetics. The goal of the enzymatic target identification problem is to identify the set of enzymes whose knockouts lead the metabolism to a state that is close to a given goal state. Given that the size of the search space is exponential in the number of enzymes, the target identification problem is very computationally intensive. We develop efficient algorithms to solve the enzymatic target identification problem in this paper. Unlike existing algorithms, our method works for a broad set of metabolic network models. We measure the effect of the knockouts of a set of enzymes as a function of the deviation of the steady state of the pathway after their knockouts from the goal state. We develop two algorithms to find the enzyme set with minimal deviation from the goal state. The first one is a traversal approach that explores possible solutions in a systematic way using a branch and bound method. The second one uses genetic algorithms to derive good solutions from a set of alternative solutions iteratively. Unlike the former one, this one can run for very large pathways. Our experiments show that our algorithms' results follow those obtained in vitro in the literature from a number of applications. They also show that the traversal method is a good approximation of the exhaustive search algorithm and it is up to 11 times faster than the exhaustive one. This algorithm runs efficiently for pathways with up to 30 enzymes. For large pathways, our genetic algorithm can find good solutions in less than 10 minutes.
Starting Page	732
Ending Page	747
Page Count	16
File Format	PDF
ISSN	15455963
DOI	10.1109/TCBB.2010.41
Volume Number	8
Issue Number	3
Journal	IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2011-05-01
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Metabolic pathway, steady state, traversal approach, genetic algorithm.
Content Type	Text
Resource Type	Article
Subject	Genetics Biotechnology Applied Mathematics

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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