Combining hypothesis- and data-driven neuroscience modeling in FAIR workflows

  1. Olivia Eriksson  Is a corresponding author
  2. Upinder Singh Bhalla
  3. Kim T Blackwell
  4. Sharon M Crook
  5. Daniel Keller
  6. Andrei Kramer
  7. Marja-Leena Linne
  8. Ausra Saudargienė
  9. Rebecca C Wade
  10. Jeanette Hellgren Kotaleski  Is a corresponding author
  1. Science for Life Laboratory, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Sweden
  2. National Center for Biological Sciences, Tata Institute of Fundamental Research, India
  3. Department of Bioengineering, Volgenau School of Engineering, George Mason University, United States
  4. School of Mathematical and Statistical Sciences, Arizona State University, United States
  5. Blue Brain Project, École Polytechnique Fédérale de Lausanne, Switzerland
  6. Department of Neuroscience, Karolinska Institute, Sweden
  7. Faculty of Medicine and Health Technology, Tampere University, Finland
  8. Neuroscience Institute, Lithuanian University of Health Sciences, Lithuania
  9. Department of Informatics, Vytautas Magnus University, Lithuania
  10. Molecular and Cellular Modeling Group, Heidelberg Institute for Theoretical Studies (HITS), Germany
  11. Center for Molecular Biology (ZMBH), ZMBH-DKFZ Alliance, University of Heidelberg, Germany
  12. Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, Germany

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  1. Olivia Eriksson
  2. Upinder Singh Bhalla
  3. Kim T Blackwell
  4. Sharon M Crook
  5. Daniel Keller
  6. Andrei Kramer
  7. Marja-Leena Linne
  8. Ausra Saudargienė
  9. Rebecca C Wade
  10. Jeanette Hellgren Kotaleski
(2022)
Combining hypothesis- and data-driven neuroscience modeling in FAIR workflows
eLife 11:e69013.
https://doi.org/10.7554/eLife.69013

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https://doi.org/10.7554/eLife.69013