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dc.contributor.authorVijayakumar, Supreetaen
dc.contributor.authorConway, Maxen
dc.contributor.authorLio, Pietroen
dc.contributor.authorAngione, Claudioen
dc.date.accessioned2019-05-29T23:30:22Z
dc.date.available2019-05-29T23:30:22Z
dc.date.issued2018-11-27en
dc.identifier.issn1477-4054
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/293226
dc.description.abstractMetabolic modelling has entered a mature phase with dozens of methods and software implementations available to the practitioner and the theoretician. It is not easy for a modeller to be able to see the wood (or the forest) for the trees. Driven by this analogy, we here present a 'forest' of principal methods used for constraint-based modelling in systems biology. This provides a tree-based view of methods available to prospective modellers, also available in interactive version at http://modellingmetabolism.net, where it will be kept updated with new methods after the publication of the present manuscript. Our updated classification of existing methods and tools highlights the most promising in the different branches, with the aim to develop a vision of how existing methods could hybridize and become more complex. We then provide the first hands-on tutorial for multi-objective optimization of metabolic models in R. We finally discuss the implementation of multi-view machine learning approaches in poly-omic integration. Throughout this work, we demonstrate the optimization of trade-offs between multiple metabolic objectives, with a focus on omic data integration through machine learning. We anticipate that the combination of a survey, a perspective on multi-view machine learning and a step-by-step R tutorial should be of interest for both the beginner and the advanced user.
dc.description.sponsorshipThis work was partially funded by a Teesside University doctoral scholarship, EPSRC, and the EU grant MIMOMICS.
dc.languageengen
dc.publisherOxford University Press
dc.rightsAll rights reserved
dc.titleSeeing the wood for the trees: a forest of methods for optimization and omic-network integration in metabolic modelling.en
dc.typeArticle
prism.endingPage1235
prism.issueIdentifier6en
prism.publicationDate2018en
prism.publicationNameBriefings in Bioinformaticsen
prism.startingPage1218
prism.volume19en
dc.identifier.doi10.17863/CAM.40376
dcterms.dateAccepted2017-04-17en
rioxxterms.versionofrecord10.1093/bib/bbx053en
rioxxterms.versionAM
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2018-11-27en
dc.contributor.orcidLio, Pietro [0000-0002-0540-5053]
dc.identifier.eissn1477-4054
rioxxterms.typeJournal Article/Reviewen
cam.issuedOnline2017-05-30en
rioxxterms.freetoread.startdate2019-11-30


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