Author

Amir Haji‐Akbari

Yale UniversityORCID 0000-0002-2228-6957Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Approach:deep learning· 2 Research Focus:protein folding & dynamics· 2 Approach:statistical model· 2 Organism:human· 1 Assay:protein structure· 1 Assay:proteomics· 1

Frequent Co-Authors

Betül UralcaniD· 2 shared Arlind KaciraniiD· 1 shared Manuel Alejandro López· 1 shared Tiago S. Domingues· 1 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

4 top collaborators · 4 mutual co-author links

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2 shared papersBiophysics

Betül UralcanORCID

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2 papers

Recent·Most cited

BiophysicsbioRxivPreprintMay 23, 2026

Pathway-resolved flux decomposition reveals hidden kinetic hierarchy in protein folding

Betül Uralcan, Manuel Alejandro López, Amir Haji‐Akbari

The paper introduces a framework to decompose protein folding flux into pathway-specific kinetic contributions, revealing hidden kinetic hierarchies in folding mechanisms.

DOI 10.64898/2026.05.20.726702

proteomicsdeep learning

𝕏 PostBluesky

BiochemistryThe Journal of Physical Chemistry BPeer-reviewedApr 30, 2024

Effect of Pressure on the Conformational Landscape of Human γD-crystallin from Replica Exchange Molecular Dynamics Simulations

Arlind Kacirani, Betül Uralcan, Tiago S. Domingues, Amir Haji‐Akbari

This study uses molecular dynamics simulations to examine how pressure affects the conformational landscape of human γD-crystallin, revealing pressure-induced changes in free energy basins and structural stability.

3 citations

humanprotein structure

𝕏 PostBluesky