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@ARTICLE{Dickscheid:1042712,
      author       = {Dickscheid, Timo and Gui, Xiaoyun and Simsek, Ahmet Nihat
                      and Schiffer, Christian and Mangin, Jean-Francois and
                      Leprince, Yann and Jirsa, Viktor and Bjaalie, Jan G. and
                      Leergaard, Trygve B. and Bludau, Sebastian and Amunts,
                      Katrin},
      title        = {{S}iibra: {A} software tool suite for realizing a
                      {M}ultilevel {H}uman {B}rain {A}tlas from complex data
                      resources},
      journal      = {biorxiv},
      reportid     = {FZJ-2025-02658},
      year         = {2025},
      abstract     = {Computational technology opens new possibilities towards
                      understanding the complexity of the human brain, but it
                      requires integrating measurements from different modalities
                      and scales in anatomical context and exposing them in
                      interoperable, actionable form. Especially with growing big
                      data resources, accessing information from different scales
                      and modalities coherently for visual exploration,
                      reproducible analysis and application development remains
                      challenging. We present siibra, a tool suite that connects
                      diverse data from cloud resources to reference atlases and
                      coordinate spaces. It supports different use cases by making
                      contents accessible through a web viewer, Python library and
                      HTTP API. Using siibra we implemented a Multilevel Human
                      Brain Atlas linking macro-anatomical concepts and their
                      inter-subject variability with measurements of the
                      microstructural composition and intrinsic variance of brain
                      regions, building on cytoarchitecture as a reference and
                      supporting MRI-based and microscopic templates. The atlas is
                      integrated with the EBRAINS research infrastructure. All
                      software and content are openly accessible.},
      cin          = {INM-1},
      cid          = {I:(DE-Juel1)INM-1-20090406},
      pnm          = {5254 - Neuroscientific Data Analytics and AI (POF4-525) /
                      HIBALL - Helmholtz International BigBrain Analytics and
                      Learning Laboratory (HIBALL) (InterLabs-0015) / EBRAINS 2.0
                      - EBRAINS 2.0: A Research Infrastructure to Advance
                      Neuroscience and Brain Health (101147319) / HBP SGA3 - Human
                      Brain Project Specific Grant Agreement 3 (945539) / DFG
                      project G:(GEPRIS)501864659 - NFDI4BIOIMAGE - Nationale
                      Forschungsdateninfrastruktur für Mikroskopie und
                      Bildanalyse (501864659) / DFG project G:(GEPRIS)313856816 -
                      SPP 2041: Computational Connectomics (313856816)},
      pid          = {G:(DE-HGF)POF4-5254 / G:(DE-HGF)InterLabs-0015 /
                      G:(EU-Grant)101147319 / G:(EU-Grant)945539 /
                      G:(GEPRIS)501864659 / G:(GEPRIS)313856816},
      typ          = {PUB:(DE-HGF)25},
      doi          = {10.1101/2025.05.20.655042},
      url          = {https://juser.fz-juelich.de/record/1042712},
}