bioRxiv · 10.1101/2025.03.21.644517
FAIRification of computational models in biology
Abstract
Computational models are essential for studying complex systems which, particularly in clinical settings, need to be quality-approved and transparent. To enhance the communication of a models features and capabilities, we propose an adaptation of the Findability, Accessibility, Interoperability and Reusability (FAIR) indicators published by the Research Data Alliance to assess models encoded in domain-specific standards, such as those established by COMBINE. The assessments guide FAIRification and add value to models.
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Balaur, I., Nickerson, D. P., Welter, D., Wodke, J. A. H., Ancien, F., Gebhardt, T., Groues, V., Hermjakob, H., Konig, M., Radde, N., Rougny, A., Schneider, R., Malik Sheriff, R. S., Shiferaw, K. B., Stefan, M., Satagopam, V. P., Waltemath, D.. 2025-03-24. FAIRification of computational models in biology. https://doi.org/10.1101/2025.03.21.644517
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