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Artificial intelligence in epigenetic studies: shedding light on rare diseases

2021-05-05Journal article Open access
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dc.contributor.authorBrasil, Sandra
dc.contributor.authorNeves, Cátia José
dc.contributor.authorRijoff, Tatiana
dc.contributor.authorFalcão, Marta
dc.contributor.authorValadão Matias, Gonçalo
dc.contributor.authorVideira, P A
dc.contributor.authorFerreira, Vanessa dos Reis
dc.date.accessioned2021-06-04T09:15:16Z
dc.date.available2021-06-04T09:15:16Z
dc.date.issued2021-05-05
dc.description.abstractMore than 7,000 rare diseases (RDs) exist worldwide, affecting approximately 350 million people, out of which only 5% have treatment. The development of novel genome sequencing techniques has accelerated the discovery and diagnosis in RDs. However, most patients remain undiagnosed. Epigenetics has emerged as a promise for diagnosis and therapies in common disorders (e.g., cancer) with several epimarkers and epidrugs already approved and used in clinical practice. Hence, it may also become an opportunity to uncover new disease mechanisms and therapeutic targets in RDs. In this "big data" age, the amount of information generated, collected, and managed in (bio)medicine is increasing, leading to the need for its rapid and efficient collection, analysis, and characterization. Artificial intelligence (AI), particularly deep learning, is already being successfully applied to analyze genomic information in basic research, diagnosis, and drug discovery and is gaining momentum in the epigenetic field. The application of deep learning to epigenomic studies in RDs could significantly boost discovery and therapy development. This review aims to collect and summarize the application of AI tools in the epigenomic field of RDs. The lower number of studies found, specific for RDs, indicate that this is a field open to expansion, following the results obtained for other more common disorders.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationBRASIL, Sandra; [et al] – Artificial intelligence in epigenetic studies: shedding light on rare diseases. Frontiers in Molecular Biosciences. eISSN 2296-889X. Vol. 8 (2021), pp. 1-14pt_PT
dc.identifier.doi10.3389/fmolb.2021.648012pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.21/13414
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherFRONTIERS MEDIA SApt_PT
dc.subjectEpigeneticspt_PT
dc.subjectEpigenomicpt_PT
dc.subjectArtificial intelligencept_PT
dc.subjectMachine learningpt_PT
dc.subjectPersonalized medicinept_PT
dc.subjectRare diseases (RD)pt_PT
dc.titleArtificial intelligence in epigenetic studies: shedding light on rare diseasespt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage14pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.titleFrontiers in Molecular Biosciencespt_PT
oaire.citation.volume8pt_PT
person.familyNameArduim Brasil
person.familyNameValadão Matias
person.familyNameVideira
person.givenNameSandra Dolores
person.givenNameGonçalo
person.givenNamePaula
person.identifier.ciencia-idB616-6C8F-F9BC
person.identifier.ciencia-id361E-C437-12DC
person.identifier.ciencia-id591D-F82C-45C2
person.identifier.orcid0000-0003-3977-7872
person.identifier.orcid0000-0001-5343-9269
person.identifier.orcid0000-0001-5987-2485
person.identifier.scopus-author-id8865647400
person.identifier.scopus-author-id6507125652
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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relation.isAuthorOfPublication46c55c4b-a935-4faf-95f5-0cf27239798a
relation.isAuthorOfPublication55d66595-59e9-4dd0-8e93-d1dab019fea5
relation.isAuthorOfPublication.latestForDiscovery55d66595-59e9-4dd0-8e93-d1dab019fea5

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