Author

Kolja Stahl

Technische Universität BerlinORCID 0000-0002-9990-7643Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:protein structure prediction· 2 Approach:deep learning· 1 Approach:experimental assay· 1 Assay:protein structure· 1 Assay:proteomics· 1

Frequent Co-Authors

Juri RappsilberiD· 2 shared Björn Hormes· 1 shared Edward RullmanniD· 1 shared Eva AbsmeieriD· 1 shared Francis J. O’ReillyiD· 1 shared James A. W. Stowell· 1 shared Jörg StülkeiD· 1 shared Kendra NjoiD· 1 shared

Activity by Year

2024-2024 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 27 mutual co-author links

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2 shared papersBioinformatics

Juri RappsilberORCID

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2 papers

Recent·Most cited

Modelling protein complexes with crosslinking mass spectrometry and deep learning

Kolja Stahl, Robert Warneke, Lorenz Demann, Rica Bremenkamp, Björn Hormes, Oliver Brock, Jörg Stülke, Juri Rappsilber

The paper improves deep learning-based structure modelling of protein complexes by integrating crosslinking mass spectrometry data, enhancing performance on challenging targets.

Nature Communications · Sep 9, 2024Peer-reviewedBioinformatics

Molecular insights into dynamic protein structures by high-contrast crosslinking mass spectrometry

Zhuo Angel Chen, Eva Absmeier, James A. W. Stowell, Ludwig Roman Sinn, Shabih Shakeel, Tamara Sijacki, Kendra Njo, Kolja Stahl, Edward Rullmann, Francis J. O’Reilly, Lori A. Passmore, Juri Rappsilber

This paper improves crosslinking mass spectrometry by using diazirine-based photo-crosslinking to better study dynamic protein regions and their conformational changes.

bioRxiv · Sep 2, 2024 · PreprintMolecular Biology