Niarakis, A;
Waltemath, D;
Glazier, J;
Schreiber, F;
Keating, SM;
Nickerson, D;
Chaouiya, C;
... Calzone, L; + view all
(2022)
Addressing barriers in comprehensiveness, accessibility, reusability, interoperability and reproducibility of computational models in systems biology.
Briefings in Bioinformatics
, 23
(4)
, Article bbac212. 10.1093/bib/bbac212.
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Abstract
Computational models are often employed in systems biology to study the dynamic behaviours of complex systems. With the rise in the number of computational models, finding ways to improve the reusability of these models and their ability to reproduce virtual experiments becomes critical. Correct and effective model annotation in community-supported and standardised formats is necessary for this improvement. Here, we present recent efforts toward a common framework for annotated, accessible, reproducible and interoperable computational models in biology, and discuss key challenges of the field.
| Type: | Article |
|---|---|
| Title: | Addressing barriers in comprehensiveness, accessibility, reusability, interoperability and reproducibility of computational models in systems biology |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1093/bib/bbac212 |
| Publisher version: | https://doi.org/10.1093/bib/bbac212 |
| Language: | English |
| Additional information: | This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third-party material in this article are included in the Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
| Keywords: | Community standards, computational modelling, model annotations, reproducibility, systems biology, Computational Biology, Computer Simulation, Reproducibility of Results, Systems Biology |
| UCL classification: | UCL |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10158980 |
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