Author

Istvan Zoltan Reguly

Pázmány Péter Catholic UniversityORCID 0000-0002-4385-4204Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Neuroscience· 1 Pharmacology & Toxicology· 1

Signature Assays, Organisms & Methods

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Approach:biophysical modeling· 1 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1

Frequent Co-Authors

András EckeriD· 1 shared Attila Csikász-NagyiD· 1 shared Erzsébet FichóiD· 1 shared Gergely SzabóiD· 1 shared János SzalmaiD· 1 shared Michael B. GilesiD· 1 shared Moisés Hernández-FernándeziD· 1 shared Saâd JbabdiiD· 1 shared

Activity by Year

2018-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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1 shared paperPharmacology & Toxicology

András EckerORCID

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2 papers

Recent·Most cited

Digital Twin Approaches for Interpretable Side Effect Prediction in Drug Discovery

András Ecker, Gergely Szabó, János Szalma, Erzsébet Fichó, Istvan Zoltan Reguly, Attila Csikász-Nagy

This paper proposes a digital twin-based model for interpretable side effect prediction in drug discovery using off-target proteins and biophysical mechanisms, offering actionable insights.

Drug Discovery Today · Mar 10, 2026Peer-reviewedPharmacology & Toxicology

Using GPUs to accelerate computational diffusion MRI: From microstructure estimation to tractography and connectomes

Moisés Hernández-Fernández, Istvan Zoltan Reguly, Saâd Jbabdi, Michael B. Giles, Stephen M. Smith, Stamatios N. Sotiropoulos

This paper presents GPU-accelerated frameworks for diffusion MRI applications, achieving significant speedups in microstructure estimation and tractography.

NeuroImage · Dec 8, 2018Peer-reviewedNeuroscience