Author Beißbarth, Tim
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2021 | Book Chapter
Predicting the Effect of Variants of Unknown Significance in Molecular Tumor Boards with the VUS-Predict Pipeline
Schlotzig, V.; Kornrumpf, K.; König, A.; Tucholski, T.; Hügel, J.; Overbeck, T. R.& Beissbarth, T. et al. (2021)
In:Röhrig, Rainer; Beißbarth, Tim; König, Jochem; Ose, Claudia; Rauch, Geraldine; Sax, Ulrich; Schreiweis, Björn, et al. (Eds.), German Medical Data Sciences 2021: Digital Medicine: Recognize – Understand – Heal : Proceedings of the Joint Conference of the 66th Annual Meeting of the German Association of Medical Informatics, Biometry, and Epidemiology e.V. (gmds) and the 13th Annual Meeting of the TMF – Technology, Methods, and Infrastructure for Networked Medical Research e.V. 2021 online in Kiel, Germany. IOS Press. DOI: https://doi.org/10.3233/SHTI210562
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2021 | Conference Proceedings
German Medical Data Sciences: Proceedings of the Joint Annual Meeting of the German Association of Medical Informatics, Biometry and Epidemiology (gmds E. V. ) and the Central European Network - International Biometric Society (CEN-IBS) 2020 in Berlin, Germany
Röhrig, R.; Beißbarth, T.; Brannath, W.; Prokosch, H.-U.; Schmidtmann, I.; Stolpe, S.& Zapf, A. (Eds.) (2021)
65th Annual Meeting of the German Association for Medical Informatics, Biometry and Epidemiology (GMDS), Meeting of the Central European Network (CEN: German Region, Austro-Swiss Region and Polish Region) of the International Biometric Society (IBS), Berlin; Virtual.
IOS Press.
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2021 | Journal Article |
Prognostic value of the micronucleus assay for clinical endpoints in neoadjuvant radiochemotherapy for rectal cancer
Dröge, L. H.; Hennies, S.; Lorenzen, S.; Conradi, L.-C.; Quack, H.; Liersch, T. & Helms, C. et al. (2021)
BMC Cancer, 21(1) art. 219. DOI: https://doi.org/10.1186/s12885-021-07914-5
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2021 | Journal Article |
Explaining decisions of graph convolutional neural networks: patient-specific molecular subnetworks responsible for metastasis prediction in breast cancer
Chereda, H.; Bleckmann, A.; Menck, K.; Perera-Bel, J.; Stegmaier, P.; Auer, F. & Kramer, F. et al. (2021)
Genome Medicine, 13(1) art. 42. DOI: https://doi.org/10.1186/s13073-021-00845-7
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2021 | Book Chapter
Management of Metadata Types in Basic Cardiological Research
Kusch, H. ; Kossen, R. ; Suhr, M.; Freckmann, L.; Weber, L.; Henke, C.& Lehmann, C. et al. (2021)
In:Röhrig, Rainer; Beißbarth, Tim; König, Jochem; Ose, Claudia; Rauch, Geraldine; Sax, Ulrich; Schreiweis, Björn, et al. (Eds.), German Medical Data Sciences 2021: Digital Medicine: Recognize – Understand – Heal pp. 59-68. DOI: https://doi.org/10.3233/SHTI210542
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2021 | Book Chapter
Relevant Aspects for Sustainable Open Source Pandemic Apps and Platform Deployment with Focus on Community Building
Thole, D.; Diesterhöft, T. O.; Vogel, S.; Greve, M.; Bauer, E.; Strathmann, S. & Elsner, C. et al. (2021)
In:Röhrig, Rainer; Beißbarth, Tim; König, Jochem; Ose, Claudia; Rauch, Geraldine; Sax, Ulrich; Schreiweis, Björn, et al. (Eds.), German Medical Data Sciences 2021: Digital Medicine: Recognize – Understand – Heal pp. 186-193. DOI: https://doi.org/10.3233/SHTI210559
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2021 | Book Chapter
Application of Pre-Trained Deep Learning Models for Clinical ECGs
Bender, T.; Seidler, T.; Bengel, P.; Sax, U.& Krefting, D. (2021)
In:Röhrig, Rainer; Beißbarth, Tim; König, Jochem; Ose, Claudia; Rauch, Geraldine; Sax, Ulrich; Schreiweis, Björn, et al. (Eds.), German Medical Data Sciences 2021: Digital Medicine: Recognize – Understand – Heal pp. 39-45. (Vol. 283). IOS Press. DOI: https://doi.org/10.3233/SHTI210539
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2021 | Journal Article |
WNT11/ROR2 signaling is associated with tumor invasion and poor survival in breast cancer
Menck, K.; Heinrichs, S.; Wlochowitz, D.; Sitte, M.; Noeding, H.; Janshoff, A. & Treiber, H. et al. (2021)
Journal of Experimental & Clinical Cancer Research, 40(1) art. 395. DOI: https://doi.org/10.1186/s13046-021-02187-z
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2022 | Journal Article
An Evidence Based Reporting System for Molecular Tumorboards Identifies Novel Therapeutics for T-Cell Lymphomas
Schmidt, N.; Kornrumpf, K.; Ries, L.; Chapuy, B.; Höltermann, C.; Beißbarth, T. & Dönitz, J. et al. (2022)
Blood, 140(Supplement 1) pp. 11896-11897. DOI: https://doi.org/10.1182/blood-2022-167435
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2023 | Book Chapter
Onkopipe: A Snakemake Based DNA-Sequencing Pipeline for Clinical Variant Analysis in Precision Medicine
Yang, J.; Beißbarth, T.& Dönitz, J. (2023)
In:Röhrig, Rainer; Grabe, Niels; Haag, Martin; Hübner, Ursula; Sax, Ulrich; Oliver Schmidt, Carsten; Sedlmayr, Martin, et al. (Eds.), German Medical Data Sciences 2023 – Science. Close to People. : Proceedings of the 68th Annual Meeting of the German Association of Medical Informatics, Biometry, and Epidemiology e.V. (gmds) 2023 in Heilbronn, Germany. IOS Press. DOI: https://doi.org/10.3233/SHTI230694
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2023 | Journal Article
Ensemble-GNN: federated ensemble learning with graph neural networks for disease module discovery and classification
Pfeifer, B.; Chereda, H.; Martin, R.; Saranti, A.; Clemens, S.; Hauschild, A.-C. & Beißbarth, T. et al. (2023)
Bioinformatics, 39(11) art. btad703. DOI: https://doi.org/10.1093/bioinformatics/btad703
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2023 | Journal Article
Impact of Portal Vein Resection (PVR) in Patients Who Underwent Curative Intended Pancreatic Head Resection
Bernhardt, M.; Rühlmann, F.; Azizian, A.; Kölling, M. A.; Beißbarth, T.; Grade, M. & König, A. O. et al. (2023)
Biomedicines, 11(11) pp. 3025. DOI: https://doi.org/10.3390/biomedicines11113025
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2023 | Journal Article |
Molecular differences of angiogenic versus vessel co-opting colorectal cancer liver metastases at single-cell resolution
Fleischer, J. R.; Schmitt, A. M.; Haas, G.; Xu, X.; Zeisberg, E. M.; Bohnenberger, H. & Küffer, S. et al. (2023)
Molecular Cancer, 22(1) art. 17. DOI: https://doi.org/10.1186/s12943-023-01713-1
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2024 | Journal Article
Histological assessment of cardiac amyloidosis in patients undergoing transcatheter aortic valve replacement
Beuthner, B. E.; Elkenani, M.; Evert, K.; Mustroph, J.; Jacob, C. F.; Paul, N. B. & Beißbarth, T. et al. (2024)
ESC Heart Failure, art. ehf2.14709. DOI: https://doi.org/10.1002/ehf2.14709
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2024 | Journal Article
A novel method to efficiently differentiate human osteoclasts from blood-derived monocytes
Chandrabalan, S.; Dang, L.; Hansen, U.; Timmen, M.; Wehmeyer, C.; Stange, R. & Beißbarth, T. et al. (2024)
Biological Procedures Online, 26(1). DOI: https://doi.org/10.1186/s12575-024-00233-6
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