Document Type
Article
Publication Date
3-27-2026
Abstract
Guidelines for managing scientific data have been established under the FAIR principles, requiring that data be Findable, Accessible, Interoperable, and Reusable. In many scientific disciplines, especially computational biology, both data and models are key to progress. For this reason, and recognizing that such models are a very special type of "data", we argue that computational models, especially mechanistic models prevalent in medicine, physiology and systems biology, deserve a complementary set of guidelines. We propose the CURE principles, emphasizing that models should be Credible, Understandable, Reproducible, and Extensible. We delve into each principle, discussing verification, validation, and uncertainty quantification for model credibility; the clarity of model descriptions and annotations for understandability; adherence to standards and open science practices for reproducibility; and the use of open standards and modular code for extensibility and reuse. We outline recommended and baseline requirements for each aspect of CURE, aiming to enhance the impact and trustworthiness of computational models, particularly in biomedical applications where credibility is paramount. Our perspective underscores the need for a more disciplined approach to modeling, aligning with emerging trends such as Digital Twins and emphasizing the importance of data and modeling standards for interoperability and reuse. Finally, we emphasize that given the non-trivial effort required to implement the guidelines, the community should strive to automate as many of the guidelines as possible.
Recommended Citation
Sauro, Herbert M.; Agmon, Eran; Blinov, Michael L.; Gennari, John H.; Hellerstein, Joseph L.; Heydarabadipour, Adel; Jardine, Bartholomew E.; May, Elebeoba; Nickerson, David P.; Smith, Lucian P.; Bader, Gary D.; Bergmann, Frank T.; Boyle, Patrick M.; Dräger, Andreas; Faeder, James R.; Feng, Song; Freire, Juliana; Fröhlich, Fabian; Glazier, James A.; Gorochowski, Thomas E.; Helikar, Tomas; Hermjakob, Henning; Hoops, Stefan; Hunter, Peter; Imoukhuede, Princess I.; Keating, Sarah M.; König, Matthias; Laubenbacher, Reinhard; Loew, Leslie M.; Lopez, Carlos F.; Lytton, William W.; Malik-Sheriff, Rahuman S.; McCulloch, Andrew; Mendes, Pedro; Mulugeta, Lealem; Myers, Chris J.; Myers, Jerry G.; Niarakis, Anna; van Niekerk, David D.; Olivier, Brett G.; Patrie, Alexander A.; Quardokus, Ellen M.; Radde, Nicole; Rohwer, Johann M.; Sahle, Sven; Schaff, James C.; Schreiber, Falk; Sego, T. J.; Shin, Janis; Snoep, Jacky L.; Vadigepalli, Rajanikanth; Wiley, H. Steven; Waltemath, Dagmar; and Moraru, Ion I., "From FAIR to CURE: Guidelines for Computational Models of Biological Systems" (2026). Computational Medicine Center Faculty Papers. Paper 68.
https://jdc.jefferson.edu/tjucompmedctrfp/68
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
PubMed ID
41888157
Language
English
Comments
This article is the author’s final published version in npj Systems Biology and Applications, Volume 12, Issue 1, 2026, Article number 77.
The published version is available at https://doi.org/10.1038/s41540-026-00651-0. Copyright © The Author(s) 2026.