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@ARTICLE{Schirner:906622,
author = {Schirner, Michael and Domide, Lia and Perdikis, Dionysios
and Triebkorn, Paul and Stefanovski, Leon and Pai, Roopa and
Prodan, Paula and Valean, Bogdan and Palmer, Jessica and
Langford, Chloê and Blickensdörfer, André and van der
Vlag, Michiel and Diaz-Pier, Sandra and Peyser, Alexander
and Klijn, Wouter and Pleiter, Dirk and Nahm, Anne and
Schmid, Oliver and Woodman, Marmaduke and Zehl, Lyuba and
Fousek, Jan and Petkoski, Spase and Kusch, Lionel and
Hashemi, Meysam and Marinazzo, Daniele and Mangin,
Jean-François and Flöel, Agnes and Akintoye, Simisola and
Stahl, Bernd Carsten and Cepic, Michael and Johnson, Emily
and Deco, Gustavo and McIntosh, Anthony R. and Hilgetag,
Claus C. and Morgan, Marc and Schuller, Bernd and Upton,
Alex and McMurtrie, Colin and Dickscheid, Timo and Bjaalie,
Jan G. and Amunts, Katrin and Mersmann, Jochen and Jirsa,
Viktor and Ritter, Petra},
title = {{B}rain simulation as a cloud service: {T}he {V}irtual
{B}rain on {EBRAINS}},
journal = {NeuroImage},
volume = {251},
issn = {1053-8119},
address = {Orlando, Fla.},
publisher = {Academic Press},
reportid = {FZJ-2022-01558},
pages = {118973 -},
year = {2022},
abstract = {The Virtual Brain (TVB) is now available as open-source
services on the cloud research platform EBRAINS
(ebrains.eu). It offers software for constructing,
simulating and analysing brain network models including the
TVB simulator; magnetic resonance imaging (MRI) processing
pipelines to extract structural and functional brain
networks; combined simulation of large-scale brain networks
with small-scale spiking networks; automatic conversion of
user-specified model equations into fast simulation code;
simulation-ready brain models of patients and healthy
volunteers; Bayesian parameter optimization in epilepsy
patient models; data and software for mouse brain
simulation; and extensive educational material. TVB cloud
services facilitate reproducible online collaboration and
discovery of data assets, models, and software embedded in
scalable and secure workflows, a precondition for research
on large cohort data sets, better generalizability, and
clinical translation.},
cin = {INM-1 / JSC},
ddc = {610},
cid = {I:(DE-Juel1)INM-1-20090406 / I:(DE-Juel1)JSC-20090406},
pnm = {5254 - Neuroscientific Data Analytics and AI (POF4-525) /
5111 - Domain-Specific Simulation $\&$ Data Life Cycle Labs
(SDLs) and Research Groups (POF4-511) / 5112 - Cross-Domain
Algorithms, Tools, Methods Labs (ATMLs) and Research Groups
(POF4-511) / 5121 - Supercomputing $\&$ Big Data Facilities
(POF4-512) / HBP SGA3 - Human Brain Project Specific Grant
Agreement 3 (945539) / HBP SGA2 - Human Brain Project
Specific Grant Agreement 2 (785907) / SLNS - SimLab
Neuroscience (Helmholtz-SLNS)},
pid = {G:(DE-HGF)POF4-5254 / G:(DE-HGF)POF4-5111 /
G:(DE-HGF)POF4-5112 / G:(DE-HGF)POF4-5121 /
G:(EU-Grant)945539 / G:(EU-Grant)785907 /
G:(DE-Juel1)Helmholtz-SLNS},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:35131433},
UT = {WOS:000766358200010},
doi = {10.1016/j.neuroimage.2022.118973},
url = {https://juser.fz-juelich.de/record/906622},
}