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dc.contributor.authorDe Bastiani, Marco Antôniopt_BR
dc.contributor.authorPfaffenseller, Biancapt_BR
dc.contributor.authorKlamt, Fabiopt_BR
dc.date.accessioned2018-09-26T02:34:08Zpt_BR
dc.date.issued2018pt_BR
dc.identifier.issn1663-9812pt_BR
dc.identifier.urihttp://hdl.handle.net/10183/182740pt_BR
dc.description.abstractDrug discovery is a very expensive and time-consuming endeavor. Fortunately, recent omics technologies and Systems Biology approaches introduced interesting new tools to achieve this task, facilitating the repurposing of already known drugs to new therapeutic assignments using gene expression data and bioinformatics. The inherent role of transcription factors in gene expression modulation makes them strong candidates for master regulators of phenotypic transitions. However, transcription factors expression itself usually does not reflect its activity changes due to posttranscriptional modifications and other complications. In this aspect, the use of high-throughput transcriptomic data may be employed to infer transcription factorstargets interactions and assess their activity through co-expression networks, which can be further used to search for drugs capable of reverting the gene expression profile of pathological phenotypes employing the connectivity maps paradigm. Following this idea, we argue that a module-oriented connectivity map approach using transcription factors-centered networks would aid the query for new repositioning candidates. Through a brief case study, we explored this idea in bipolar disorder, retrieving known drugs used in the usual clinical scenario as well as new candidates with potential therapeutic application in this disease. Indeed, the results of the case study indicate just how promising our approach may be to drug repositioning.en
dc.format.mimetypeapplication/pdfpt_BR
dc.language.isoengpt_BR
dc.relation.ispartofFrontiers in Pharmacology. Lausanne. Vol. 9, no. 9 (July 2018), article 697 p. 1-9pt_BR
dc.rightsOpen Accessen
dc.subjectTranstorno bipolarpt_BR
dc.subjectConnectivity mapen
dc.subjectComputational drug repositioningen
dc.subjectReposicionamento de medicamentospt_BR
dc.subjectMaster regulatorsen
dc.subjectFatores de transcriçãopt_BR
dc.subjectTranscription factorsen
dc.subjectEngenharia reversapt_BR
dc.subjectBiologia computacionalpt_BR
dc.subjectReverse engineeringen
dc.subjectSystems pharmacologyen
dc.titleMaster regulators connectivity map : a transcription factors-centered approach to drug repositioningpt_BR
dc.typeArtigo de periódicopt_BR
dc.identifier.nrb001074855pt_BR
dc.type.originEstrangeiropt_BR


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