Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/56936

TitleOptFlux: an open-source software platform for in silico metabolic engineering
Author(s)Rocha, I.
Maia, Paulo
Pinto, José Pedro Basto Gouveia Pereira
Vilaça, Paulo Ricardo Carvalho
Soares, Simão Pedro Pinho
Nielsen, J.
Patil, K. R.
Ferreira, Eugénio C.
Rocha, Miguel
Evangelista, Pedro Tiago
Issue date22-Mar-2010
CitationRocha, Isabel; Maia, Paulo; Evangelista, P.; Vilaça, P.; Simão Soares; Pinto, J. P.; Nielsen, J.; Patil, K. R.; Ferreira, Eugénio C.; Rocha, Miguel, OptFlux: an open-source software platform for in silico metabolic engineering. International Symposium on Integrative Bioinformatics - 6th Annual Meeting. Cambridge, UK, 22nd-24th March, 2010.
Abstract(s)OptFlux is a new platform aimed at being the reference computational tool for Metabolic Engineering (ME) applications. It allows the use of stoichiometric models of microbial metabolism for simulationandoptimizationpurposes.ME deals with designingorganismswith enhancedcapabilitiesregarding the productivities ofdesired compounds. Different approaches have been used to aid in ME efforts taking available models of metabolism and mathematical tools and/or experimental data to identify metabolic bottlenecks or targets for genetic engineering. However, the rational design of microbial strains has been limited to the developers of the computational/mathematical techniques, since a platform that provides a userfriendly interfaceto perform suchtaskswas notyet available. Tochangethis scenario,we introduce the OptFlux,whose mainfeaturesare: - Open-source– userscanusethe tool freely andinvites thecontribution ofotherresearchers; - User-friendly –facilitates its usebyuserswith no/little backgroundin modelling/informatics; - Modular – facilitates the addition ofnewfeatures; - Compatiblewith standards–compatibilitywith the SystemsBiologyMarkup Language(SBML) and the layout informationofCellDesigner. Currently, the methods implemented for the simulation of wild-type or mutant strains are Flux Balance Analysis, Minimization of Metabolic Adjustment (MOMA), and Regulatory on/off Minimization ofMetabolic flux changes(ROOM). The optimization tasks, i.e., the identification of metabolic engineering targets can be performed with Evolutionary Algorithms or Simulated Annealing[1,2]. Furthermore, the software includes plug-ins to handleElementaryFluxModes andMetabolic FluxAnalysis. Thesoftware is madeavailable, togetherwith otherresources,in the homepage:http://www.optflux.org.
TypePoster
URIhttp://hdl.handle.net/1822/56936
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CEB - Painéis em Conferências / Posters in Conferences

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