Author

Ralf Hausmann

Universitätsklinikum AachenORCID 0000-0002-0130-110XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Biophysics· 1 Neuroscience· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Approach:experimental assay· 2 Assay:bulk RNA-seq· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Assay:electrophysiology· 1 Approach:machine learning (classical)· 1 Research Focus:protein folding & dynamics· 1

Frequent Co-Authors

Angelika LampertiD· 2 shared Günther Schmalzing· 2 shared Petra A. I. Hautvast· 2 shared Silvia Detro‐Dassen· 2 shared Alexander BartholomäusiD· 1 shared Alexander DiltheyiD· 1 shared Alexander GoesmanniD· 1 shared Amdiya Botchoi· 1 shared

Activity by Year

2020-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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2 shared papersBiophysics

Angelika LampertORCID

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Author profile →

3 papers

Recent·Most cited

Outer Pore Collapse as a Potential Mechanism of Partial Loss of Pain in Nav1.7 M899I

Vishal Sudha Bhagavath Eswaran, Estefania Torres-Ortiz, Petra A. I. Hautvast, Amdiya Botchoi, Silvia Detro‐Dassen, Anika Neureiter, Yi Liu, Ralf Hausmann, Angelika Lampert

The paper investigates the M899I variant in Nav1.7, showing it causes pore collapse, leading to loss of sodium currents and pain insensitivity.

bioRxiv · Aug 21, 2026 · PreprintBiophysics

Swarm Learning as a privacy-preserving machine learning approach for disease classification

Stefanie Warnat‐Herresthal, Hartmut Schultze, Krishnaprasad Shastry, Sathyanarayanan Manamohan, Saikat Mukherjee, Vishesh Garg, Ravi Sarveswara, Kristian Händler, Peter Pickkers, N. Ahmad Aziz, Sofia Ira Ktena, Florian Tran, Michael Bitzer, Stephan Ossowski, Nicolas Casadei, , Alexander Goesmann

This paper introduces Swarm Learning, a decentralized machine learning approach for disease classification using transcriptomic data, demonstrating its effectiveness in developing classifiers for COVID-19, tuberculosis, and leukemias while preserving privacy.

Nature · May 26, 2021Peer-reviewedBioinformatics

Uncoupling sodium channel dimers rescues phenotype of pain-linked Nav1.7 mutation

Annika H. Rühlmann, Jannis Körner, Ralf Hausmann, Nikolay Bebrivenski, Christian Neuhof, Silvia Detro‐Dassen, Petra A. I. Hautvast, Carène Benasolo, Jannis Meents, Jan‐Philipp Machtens, Günther Schmalzing, Angelika Lampert

The paper shows that uncoupling dimerized Nav1.7 channels reduces persistent current caused by a pain mutation, suggesting dimerization plays a role in pain syndromes.

British Journal of Pharmacology · Jul 14, 2020Peer-reviewedNeuroscience