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I use an integrative approach to cardiac electrophysiology research, combining clinical and experimental data, modelling and simulation, to investigate cardiac arrhythmias and possible therapeutic targets.
Due to the multiscale nature of cardiac electrophysiology, computational models represent the perfect framework to augment and fully analyse experimental and clinical findings. They allow for the integration of existing and new knowledge, enabling investigations of cellular processes and cardiac arrhythmias with high spatio-temporal resolution. Such an approach involves a deep understanding of multiple data sources, from cellular ionic mechanisms and signaling pathways to electrical conduction at the tissue and whole organ levels. In order to further advance our current understanding of heart function, our methodology is based on a synergistic clinical, experimental and computational approach, aiming to develop novel hypotheses, therapeutic targets, and technologies to improve risk identification under different disease conditions. Translation of results from basic science to clinical and industrial applications is central to my work via collaboration with clinicians and industrial partners.
Interests
I use an integrative approach to cardiac electrophysiology research, combining clinical and experimental data, modelling and simulation, to investigate cardiac arrhythmias and possible therapeutic targets.
Due to the multiscale nature of cardiac electrophysiology, computational models represent the perfect framework to augment and fully analyse experimental and clinical findings. They allow for the integration of existing and new knowledge, enabling investigations of cellular processes and cardiac arrhythmias with high spatio-temporal resolution. Such an approach involves a deep understanding of multiple data sources, from cellular ionic mechanisms and signaling pathways to electrical conduction at the tissue and whole organ levels. In order to further advance our current understanding of heart function, our methodology is based on a synergistic clinical, experimental and computational approach, aiming to develop novel hypotheses, therapeutic targets, and technologies to improve risk identification under different disease conditions. Translation of results from basic science to clinical and industrial applications is central to my work via collaboration with clinicians and industrial partners.
研究兴趣
论文共 146 篇作者统计合作学者相似作者
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CoRR (2024)
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James A Coleman,Ruben Doste,Zakariye Ashkir,Raffaele Coppini, Rafael Sachetto,Hugh Watkins,Betty Raman,Alfonso Bueno-Orovio
Cardiovascular research (2024)
Albert Dasí,Claudia Nagel,Michael T.B. Pope, Rohan S. Wijesurendra,Timothy R. Betts, Rafael Sachetto,Axel Loewe,Alfonso Bueno-Orovio,Blanca Rodriguez
crossref(2024)
Jorge Corral Acero,Pablo Lamata,Ingo Eitel,Ernesto Zacur, Ruben Evertz,Torben Lange,Sören J Backhaus,Thomas Stiermaier,Holger Thiele,Alfonso Bueno-Orovio,Andreas Schuster, Vicente Grau
Medical Image Analysis (2024): 103108-103108
James A. Coleman,Ruben Doste,Matteo Beltrami,Raffaele Coppini,Iacopo Olivotto,Betty Raman,Alfonso Bueno-Orovio
COMPUTERS IN BIOLOGY AND MEDICINE (2024): 107829-107829
Nonlinear Systems and Complexity Fractional Dispersive Models and Applicationspp.31-52, (2024)
James A Coleman, Ruben Doste,Matteo Beltrami, Alessia Argirò, Raffaele Coppini,Iacopo Olivotto, Betty Raman,Alfonso Bueno-Orovio
Europaceno. Supplement_1 (2023)
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