Author

Karin Everschor‐Sitte

University of Duisburg-EssenORCID 0000-0001-8767-6633Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Assay:Hi-C· 2 Research Focus:benchmarking· 1 Research Focus:chromatin & epigenetic regulation· 1 Research Focus:dimensionality reduction· 1 Research Focus:drug response / drug discovery· 1 Assay:long-read sequencing· 1 Research Focus:protein structure prediction· 1

Frequent Co-Authors

Michael WandiD· 2 shared Stanislav SysiD· 2 shared Stephan WeißbachiD· 2 shared Susann SchweigeriD· 2 shared Susanne GerberiD· 2 shared Alejandro Ceron‐NoriegaiD· 1 shared Anne Kerber· 1 shared Azza Soliman· 1 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 39 mutual co-author links

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2 shared papersBiophysics

Michael WandORCID

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2 papers

Recent·Most cited

BiophysicsbioRxivPreprintApr 2, 2026

Correcting Preprocessing Bias in Sparse Chromatin Contact Data Enables Physically Interpretable Reconstruction of Genome Architecture

Stanislav Sys, Marcel Misak, Azza Soliman…·Susanne Gerber

The paper identifies preprocessing bias in chromatin contact data and introduces a framework to correct it, enabling physically interpretable genome architecture reconstruction.

DOI 10.64898/2026.03.31.715622

Hi-Cdeep learning

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BioinformaticsbioRxivPreprintMay 29, 2024

Direct CCUT: A Versatile and Standardized Framework to Train 3C Deep Restoration Models

Stanislav Sys, Alejandro Ceron‐Noriega, Anne Kerber…·Susanne Gerber

Direct CCUT trains deep models to reconstruct high-resolution chromatin interaction matrices from low-resolution Pore-C and 3C data using consumer GPUs.

DOI 10.1101/2024.05.29.596528

Hi-Clong-read sequencing

𝕏 PostBluesky