Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/80974

Registo completo
Campo DCValorIdioma
dc.contributor.authorOliveira, Alexandre Rafael Machadopor
dc.contributor.authorCunha, Emanuel Rodriguespor
dc.contributor.authorSilva, Miguelpor
dc.contributor.authorFaria, Cristiana Silvapor
dc.contributor.authorDias, Oscarpor
dc.date.accessioned2022-12-06T11:07:23Z-
dc.date.issued2023-
dc.identifier.citationOliveira, Alexandre; Cunha, Emanuel; Silva, Miguel; Faria, Cristiana; Dias, Oscar, Exploring Xylella fastidiosas Metabolic Traits Using a GSM Model of the Phytopathogenic Bacterium. Lecture Notes in Networks and Systems, Vol. 553, Springer Science and Business Media Deutschland GmbH, 2022. ISBN: 9783030862602por
dc.identifier.isbn978-3-031-17023-2por
dc.identifier.issn2367-3370-
dc.identifier.urihttps://hdl.handle.net/1822/80974-
dc.descriptionThe model presented in this work can be found in BioModels [26] with the identifier MODEL2205020002. To access the model: – Visit https://www.ebi.ac.uk/biomodels/login/auth. – Log in with the username reviewerForMODEL2205020002 and password DEMPB4. – Access https://www.ebi.ac.uk/biomodels/MODEL2205020002 to view the model.por
dc.descriptionFirst Online: 20 October 2022-
dc.description.abstractXylella fastidiosa is a gram-negative phytopathogenic bacterium able to infect over 500 plant species, with devastating consequences for agricultural and forest-based economies. In the last decade, genome-scale metabolic (GSM) models have become important systems biology tools for studying the metabolic behaviour of different organisms. In this work, a GSM model of X. fastidiosa subsp. pauca De Donno is presented, comprising 1164 reactions, 1379 metabolites, and 508 genes. The model was validated by comparing in silico simulations with available experimental data. The GSM model allowed identifying potential drug targets using a pipeline based on a gene essentiality analysis of the model.eng
dc.description.sponsorshipThis study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UIDB/04469/2020 unit. A. Oliveira (DFA/BD/10205/2020), E. Cunha (DFA/BD/8076/2020) hold a doctoral fellowship provided by the FCT. Oscar Dias acknowledge FCT for the Assistant Research contract obtained under CEEC Individual 2018.por
dc.language.isoengpor
dc.publisherSpringerpor
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04469%2F2020/PTpor
dc.rightsrestrictedAccesspor
dc.subjectXylella fastidiosapor
dc.subjectGSM modellingpor
dc.subjectEssentially analysispor
dc.subjectMerlinpor
dc.titleExploring Xylella fastidiosas metabolic traits using a GSM model of the phytopathogenic bacteriumpor
dc.typeconferencePaperpor
dc.peerreviewedyes-
dc.relation.publisherversionhttps://link.springer.com/bookseries/15179por
dc.commentsCEB55916por
oaire.citationStartPage79por
oaire.citationEndPage88por
oaire.citationVolume553-
dc.date.updated2022-12-05T23:25:15Z-
dc.identifier.doi10.1007/978-3-031-17024-9_8por
dc.date.embargo10000-01-01-
dc.identifier.eisbn978-3-031-17024-9-
dc.description.publicationversioninfo:eu-repo/semantics/publishedVersion-
sdum.journalLecture Notes in Networks and Systemspor
sdum.bookTitleLecture Notes in Networks and Systemspor
Aparece nas coleções:CEB - Livros e Capítulos de Livros / Books and Book Chapters

Ficheiros deste registo:
Ficheiro Descrição TamanhoFormato 
document_55916_1.pdf
Acesso restrito!
333,13 kBAdobe PDFVer/Abrir

Partilhe no FacebookPartilhe no TwitterPartilhe no DeliciousPartilhe no LinkedInPartilhe no DiggAdicionar ao Google BookmarksPartilhe no MySpacePartilhe no Orkut
Exporte no formato BibTex mendeley Exporte no formato Endnote Adicione ao seu ORCID