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

Febra, Cláudia; Saraiva, Joana; AlKhnbashi, Omer; Vaz, Fátima; Macedo, João; Uddin, Mohammed J.; Penque, Deborah; Soares, Nelson C.

http://hdl.handle.net/10400.18/11295

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Resumo(s)

Background 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.

Palavras-chave

Venous Thromboembolism Plasma Proteomic Metabolomics Red Blood Cells Genómica Funcional e Estrutural

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http://hdl.handle.net/10400.18/11295

Coleções

DGH - Apresentações orais em encontros internacionais

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