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Multiomics profiling of Red Blood Cells (RBCs) combined with Deep Machine Learning analysis – reveals potential Diagnostic Biomarkers for Acute Venous Thromboembolism

2025-05-11Documento de conferência Acesso restrito
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datacite.subject.fosCiências Naturais::Ciências Biológicas
dc.contributor.authorFebra, Cláudia
dc.contributor.authorSaraiva, Joana
dc.contributor.authorAlKhnbashi, Omer
dc.contributor.authorVaz, Fátima
dc.contributor.authorMacedo, João
dc.contributor.authorUddin, Mohammed J.
dc.contributor.authorPenque, Deborah
dc.contributor.authorSoares, Nelson C.
dc.date.accessioned2026-03-24T14:23:38Z
dc.date.available2026-03-24T14:23:38Z
dc.date.issued2025-05-11
dc.description.abstractBackground and aims: Venous Thromboembolism (VTE) is a leading cause of cardiovascular mortality. The diagnosis of acute VTE is still based on complex imaging exams due to the lack of biomarkers. However, studies assessing the diagnostic capacity of novel metabolomics biomarkers in VTE are scarce. Our aim was to determine whether patients with acute VTE exhibit differences in proteomic and metabolomic profiles.eng
dc.identifier.urihttp://hdl.handle.net/10400.18/11295
dc.language.isoeng
dc.peerreviewedyes
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectVenous Thromboembolism
dc.subjectPlasma
dc.subjectProteomic
dc.subjectMetabolomics
dc.subjectRed Blood Cells
dc.subjectGenómica Funcional e Estrutural
dc.titleMultiomics profiling of Red Blood Cells (RBCs) combined with Deep Machine Learning analysis – reveals potential Diagnostic Biomarkers for Acute Venous Thromboembolismeng
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferenceDate2025-05-11
oaire.citation.conferencePlaceDubai, United Arab Emirates
oaire.citation.title4th UAE Anatomy & Cellular Biology Conference, 10, 11 May 2025
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85

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