SOURCE-LINKED INTELLIGENCE

A Multi-Omics Approach for Novel Drug Targets, Biomarkers and Risk Algorithms for Myocardial Infarction

CORDIS · observation · Publication date unknown

alidated through various approaches including computational analysis, (using Mendelian randomisation and 10 year follow-up data), and functional work that includes using zebrafish as an animal model. Machine learning algorithms will be used to analyse the multi-layered data to identify novel biomarkers and risk algorithms, including polygenic risk scores, for early risk prediction in the clinic. Quantitative targeted proteomic assays will be developed for further validation in other cohorts facilitating clinical use. Besides the increase in knowledge on the molecular etiology of MI, this powerful integrated strategy will bring rapid clinical translation of unprecedented multi-omic data. Multi-Omics, Genomics, Transcriptomics, Metabolomics, Proteomics, Drug Targets, Biomarkers, Risk Algorithms, Myocardial Infarction, Atherosclerosis, Risk Factors, Machine Learning, Big Data

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recordType

award

status

SIGNED

region

EU

value

3999840

unit

EUR