S.K. is supported by a Tel-Hai college fellowship and the Israel Innovation Authority. S.B.W. is supported by the MCST

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S.K. is supported by a Tel-Hai college fellowship and the Israel Innovation Authority. S.B.W. is supported by the MCST

Authors

Publications

Multiomics tools for improved atherosclerotic cardiovascular disease management

Sopić, Miron; Vilne, Baiba; Gerdts, Eva; Trindade, Fábio; Uchida, Shizuka; Khatib, Soliman; Wettinger, Stephanie Bezzina; Devaux, Yvan; Magni, Paolo

(Elsevier Ltd, 2023)

TY  - JOUR
AU  - Sopić, Miron
AU  - Vilne, Baiba
AU  - Gerdts, Eva
AU  - Trindade, Fábio
AU  - Uchida, Shizuka
AU  - Khatib, Soliman
AU  - Wettinger, Stephanie Bezzina
AU  - Devaux, Yvan
AU  - Magni, Paolo
PY  - 2023
UR  - https://farfar.pharmacy.bg.ac.rs/handle/123456789/5145
AB  - Multiomics studies offer accurate preventive and therapeutic strategies for atherosclerotic cardiovascular disease (ASCVD) beyond traditional risk factors. By using artificial intelligence (AI) and machine learning (ML) approaches, it is possible to integrate multiple ‘omics and clinical data sets into tools that can be utilized for the development of personalized diagnostic and therapeutic approaches. However, currently multiple challenges in data quality, integration, and privacy still need to be addressed. In this opinion, we emphasize that joined efforts, exemplified by the AtheroNET COST Action, have a pivotal role in overcoming the challenges to advance multiomics approaches in ASCVD research, with the aim to foster more precise and effective patient care.
PB  - Elsevier Ltd
T2  - Trends in Molecular Medicine
T1  - Multiomics tools for improved atherosclerotic cardiovascular disease management
VL  - 29
IS  - 12
SP  - 983
EP  - 995
DO  - 10.1016/j.molmed.2023.09.004
ER  - 
@article{
author = "Sopić, Miron and Vilne, Baiba and Gerdts, Eva and Trindade, Fábio and Uchida, Shizuka and Khatib, Soliman and Wettinger, Stephanie Bezzina and Devaux, Yvan and Magni, Paolo",
year = "2023",
abstract = "Multiomics studies offer accurate preventive and therapeutic strategies for atherosclerotic cardiovascular disease (ASCVD) beyond traditional risk factors. By using artificial intelligence (AI) and machine learning (ML) approaches, it is possible to integrate multiple ‘omics and clinical data sets into tools that can be utilized for the development of personalized diagnostic and therapeutic approaches. However, currently multiple challenges in data quality, integration, and privacy still need to be addressed. In this opinion, we emphasize that joined efforts, exemplified by the AtheroNET COST Action, have a pivotal role in overcoming the challenges to advance multiomics approaches in ASCVD research, with the aim to foster more precise and effective patient care.",
publisher = "Elsevier Ltd",
journal = "Trends in Molecular Medicine",
title = "Multiomics tools for improved atherosclerotic cardiovascular disease management",
volume = "29",
number = "12",
pages = "983-995",
doi = "10.1016/j.molmed.2023.09.004"
}
Sopić, M., Vilne, B., Gerdts, E., Trindade, F., Uchida, S., Khatib, S., Wettinger, S. B., Devaux, Y.,& Magni, P.. (2023). Multiomics tools for improved atherosclerotic cardiovascular disease management. in Trends in Molecular Medicine
Elsevier Ltd., 29(12), 983-995.
https://doi.org/10.1016/j.molmed.2023.09.004
Sopić M, Vilne B, Gerdts E, Trindade F, Uchida S, Khatib S, Wettinger SB, Devaux Y, Magni P. Multiomics tools for improved atherosclerotic cardiovascular disease management. in Trends in Molecular Medicine. 2023;29(12):983-995.
doi:10.1016/j.molmed.2023.09.004 .
Sopić, Miron, Vilne, Baiba, Gerdts, Eva, Trindade, Fábio, Uchida, Shizuka, Khatib, Soliman, Wettinger, Stephanie Bezzina, Devaux, Yvan, Magni, Paolo, "Multiomics tools for improved atherosclerotic cardiovascular disease management" in Trends in Molecular Medicine, 29, no. 12 (2023):983-995,
https://doi.org/10.1016/j.molmed.2023.09.004 . .
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