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Julian Matschinske
Julian Matschinske
Verified email at uni-hamburg.de
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Exploring the SARS-CoV-2 virus-host-drug interactome for drug repurposing
S Sadegh, J Matschinske, DB Blumenthal, G Galindez, T Kacprowski, ...
Nature communications 11 (1), 1-9, 2020
1192020
Computational strategies to combat COVID-19: useful tools to accelerate SARS-CoV-2 and coronavirus research
F Hufsky, K Lamkiewicz, A Almeida, A Aouacheria, C Arighi, A Bateman, ...
Briefings in Bioinformatics 22 (2), 642-663, 2021
882021
Lessons from the COVID-19 pandemic for advancing computational drug repurposing strategies
G Galindez, J Matschinske, TD Rose, S Sadegh, M Salgado-Albarrán, ...
Nature Computational Science 1 (1), 33-41, 2021
612021
The AIMe registry for artificial intelligence in biomedical research
J Matschinske, N Alcaraz, A Benis, M Golebiewski, DG Grimm, L Heumos, ...
Nature Methods 18 (10), 1128-1131, 2021
162021
sPLINK: a federated, privacy-preserving tool as a robust alternative to meta-analysis in genome-wide association studies
R Nasirigerdeh, R Torkzadehmahani, J Matschinske, T Frisch, M List, ...
BioRxiv, 2020
112020
Privacy-preserving artificial intelligence techniques in biomedicine
R Torkzadehmahani, R Nasirigerdeh, DB Blumenthal, T Kacprowski, ...
Methods of Information in Medicine, 2022
92022
Exploring the SARS-CoV-2 virus-host-drug interactome for drug repurposing. Nat Commun 11: 3518
S Sadegh, J Matschinske, DB Blumenthal, G Galindez, T Kacprowski, ...
62020
HyFed: A hybrid federated framework for privacy-preserving machine learning
R Nasirigerdeh, R Torkzadehmahani, J Matschinske, J Baumbach, ...
arXiv preprint arXiv:2105.10545, 2021
52021
Individuating possibly repurposable drugs and drug targets for COVID-19 treatment through hypothesis-driven systems medicine using CoVex
J Matschinske, M Salgado-Albarrán, S Sadegh, D Bongiovanni, ...
ASSAY and Drug Development Technologies 18 (8), 348-355, 2020
42020
sPLINK: a hybrid federated tool as a robust alternative to meta-analysis in genome-wide association studies
R Nasirigerdeh, R Torkzadehmahani, J Matschinske, T Frisch, M List, ...
Genome biology 23 (1), 1-24, 2022
32022
The featurecloud ai store for federated learning in biomedicine and beyond
J Matschinske, J Späth, R Nasirigerdeh, R Torkzadehmahani, ...
arXiv preprint arXiv:2105.05734, 2021
32021
Flimma: a federated and privacy-preserving tool for differential gene expression analysis
O Zolotareva, R Nasirigerdeh, J Matschinske, R Torkzadehmahani, ...
arXiv preprint arXiv:2010.16403, 2020
22020
Towards Query-Driven Data Minimization.
PK Schwab, JO Matschinske, AM Wahl, K Meyer-Wegener
LWDA, 335-338, 2018
22018
Query-Driven Data Minimization with the DataEconomist.
PK Schwab, JO Matschinske, AM Wahl, K Meyer-Wegener
EDBT, 614-617, 2019
12019
Federated Random Forests can improve local performance of predictive models for various healthcare applications
AC Hauschild, M Lemanczyk, J Matschinske, T Frisch, O Zolotareva, ...
Bioinformatics 38 (8), 2278-2286, 2022
2022
Flimma: a federated and privacy-aware tool for differential gene expression analysis
O Zolotareva, R Nasirigerdeh, J Matschinske, R Torkzadehmahani, ...
Genome biology 22 (1), 1-26, 2021
2021
Flimma: a federated and privacy-aware tool for differential gene expression analysis
J Matschinske, M List, G Kaissis, DB Blumenthal, D Rückert, ...
Genome Biology, 2021
2021
dsMTL-a computational framework for privacy-preserving, distributed multi-task machine learning
H Cao, Y Zhang, J Baumbach, PR Burton, D Dwyer, N Koutsouleris, ...
bioRxiv, 2021
2021
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