Imperial College London
Alternate

ProfessorDanielRueckert

Faculty of Engineering, Department of Computing

Professor of Visual Information Processing
 
 
 
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Contact

 

+44 (0)20 7594 8333d.rueckert Website

 
 
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Location

 

568Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Nasirigerdeh:2022:10.1186/s13059-021-02562-1,
author = {Nasirigerdeh, R and Torkzadehmahani, R and Matschinske, J and Frisch, T and List, M and Spaeth, J and Weiss, S and Voelker, U and Pitkaenen, E and Heider, D and Wenke, NK and Kaissis, G and Rueckert, D and Kacprowski, T and Baumbach, J},
doi = {10.1186/s13059-021-02562-1},
journal = {GENOME BIOLOGY},
title = {sPLINK: a hybrid federated tool as a robust alternative to meta-analysis in genome-wide association studies},
url = {http://dx.doi.org/10.1186/s13059-021-02562-1},
volume = {23},
year = {2022}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AU  - Nasirigerdeh,R
AU  - Torkzadehmahani,R
AU  - Matschinske,J
AU  - Frisch,T
AU  - List,M
AU  - Spaeth,J
AU  - Weiss,S
AU  - Voelker,U
AU  - Pitkaenen,E
AU  - Heider,D
AU  - Wenke,NK
AU  - Kaissis,G
AU  - Rueckert,D
AU  - Kacprowski,T
AU  - Baumbach,J
DO  - 10.1186/s13059-021-02562-1
PY  - 2022///
SN  - 1474-760X
TI  - sPLINK: a hybrid federated tool as a robust alternative to meta-analysis in genome-wide association studies
T2  - GENOME BIOLOGY
UR  - http://dx.doi.org/10.1186/s13059-021-02562-1
UR  - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000746617100003&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=a2bf6146997ec60c407a63945d4e92bb
VL  - 23
ER  -
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