Please use this identifier to cite or link to this item: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/5909
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dc.contributor.authorSharma, Arun-
dc.contributor.authorChanumolu, Sree Krishna [Guided by]-
dc.date.accessioned2022-08-21T05:46:55Z-
dc.date.available2022-08-21T05:46:55Z-
dc.date.issued2015-
dc.identifier.urihttp://ir.juit.ac.in:8080/jspui//xmlui/handle/123456789/5909-
dc.description.abstractRenewed interest in metabolic research over the last two decades has inspired an explosion of technological developments for studying metabolism. At the forefront of methodological innovation is an approach referred to as "untargeted" or "discovery" metabolomics. We are referring KEGG data base to get the pathways information as an input which is present in the in XML format. Main aim is to calculate the rate of the reaction which are present in the reaction which is a simulation of the real world reactions. The algorithm platform developed for integration of KEGG data with a method to find the rate of the reaction of all the reaction occurring in the pathways. In this algorithm we are using the Stoichiomatric matrix to find the rate, which can be further use to decide which reaction to be eliminated or which product to be added to get better the results.en_US
dc.language.isoenen_US
dc.publisherJaypee University of Information Technology, Solan, H.P.en_US
dc.subjectMetabolic networksen_US
dc.subjectAnabolic pathwayen_US
dc.subjectGlycolysisen_US
dc.subjectGeneric systemen_US
dc.subjectFlux balance analysisen_US
dc.titleDevelopment of Generic System Synthetic Biology Simulation Network using Metabolic Flux Balance Analysisen_US
dc.typeProject Reporten_US
Appears in Collections:B.Tech. Project Reports



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