Akademik Veri Yönetim Sistemi
Magni P., Devaux Y., Kilinç E.
TÜBİTAK - AB COST Projesi , 2022 - 2026
The latest epidemiological data suggest that cardiovascular diseases (CVD) are still the leading cause of
morbidity and mortality worldwide. In order to improve the CVD outcomes, we need new strategies that
incorporate the complex interplay of different driving forces behind atherosclerosis pathophysiology in
addition to the traditional risk factors. AtheroNET aims to consolidate and connect experts from different
fields into European and international network that will focus on the use of multiple omics technologies and
data integration through machine learning/artificial intelligence ML/AI approach to bring novel paradigms in
prevention, diagnosis, and treatment of atherosclerotic cardiovascular disease (ASCVD). Current
CVDrelated
initiatives and networks are focused on specific aspects of CVD and/or specific methodologies.
AtheroNET offers a comprehensive environment in which different stakeholders (basic scientists, clinicians,
bioinformaticians, industry representatives, patients’ representatives) will address current challenges by:
Organizing multi-centric studies for cross-validation of different genomic, transcriptomic, proteomic,
and metabolomics traits related to atherosclerosis;
Fostering joined research efforts through different European funds to investigate novel
pathophysiological mechanisms, prognostic, diagnostic, and therapeutic ASCVD targets;
Inter-sectorial cooperation with the private sector to commercialize novel scientific achievements and
secure their delivery to the market;
Organizing inter-laboratory dialogs and ring trials leading to standardization and harmonization of
different wet-lab and dry-lab workflows;
Utilizing specific ML/AI algorithms for data integration and design of innovative multiomics models.
Through the abovementioned steps, the Action will train the next generation of scientists ready to tackle
upcoming challenges and provide opportunities for the transfer of novel omics technologies from bench to
the bedside.