Author

Georg Pabst

University of GrazORCID 0000-0003-1967-1536Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:Bayesian inference· 1 Research Focus:protein folding & dynamics· 1 Approach:simulation· 1 Research Focus:software / tool· 1 Approach:statistical model· 1 Assay:structural biology· 1

Frequent Co-Authors

Enrico F. SemeraroiD· 2 shared Ladislav BartošiD· 1 shared Paulina PilleriD· 1 shared Rahul DebiD· 1 shared Robert VáchaiD· 1 shared Sandro KelleriD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

6 top collaborators · 15 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersBiophysics

Enrico F. SemeraroORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

BiophysicsbioRxivPreprintJul 8, 2026

Membrane Thickness Strain from Protein Inclusions: A Multiscale Simulation and X-Ray Scattering Study of Proteoliposomes

Enrico F. Semeraro, Ladislav Bartoš, Paulina Piller…·Georg Pabst

This study uses multiscale simulations and X-ray scattering to quantify membrane strain caused by protein inclusions in proteoliposomes, showing agreement between simulations and experiments.

DOI 10.64898/2026.07.03.736288

structural biologystatistical model

𝕏 PostBluesky

BiophysicsbioRxivPreprintJul 2, 2026

SAS_MoCa: a software for small-angle scattering data analysis of large unilamellar vesicles

Enrico F. Semeraro, Georg Pabst

SAS_MoCa is an open-source Python package for analyzing small-angle scattering data from large unilamellar vesicles, providing posterior parameter distributions and uncertainties using a Bayesian framework.

DOI 10.64898/2026.06.29.735169

Bayesian inferencesoftware / tool

𝕏 PostBluesky