An algorithm to detect and communicate the differences in computational models describing biological systems
- Published
- Accepted
- Subject Areas
- Computational Biology, Computational Science
- Keywords
- model reuse, difference detection, version control, reproducibility, model management, SBML, CellML
- Copyright
- © 2014 Scharm et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
- Cite this article
- 2014. An algorithm to detect and communicate the differences in computational models describing biological systems. PeerJ PrePrints 2:e640v1 https://doi.org/10.7287/peerj.preprints.640v1
Abstract
Repositories, such as the BioModels Database and the Physiome Model Repository support the reuse of models and ensure transparency about results in publications linked to those models. With thousands of models available, a framework to track the differences between models and their versions is essential to compare and combine models. Difference detection allows users to study the history of models but also helps in the detection of errors and inconsistencies. However, current repositories lack suitable methods to track a model’s development over time. Consequently, researchers have problems to grasp the differences between models and their versions.
Focusing on SBML and CellML, we developed an algorithm to accurately detect and describe differences between versions of a model with respect to (i) the models’ encoding, (ii) the structure of biological networks, and (iii) mathematical expressions. Our method is implemented in a comprehensive and open library called BiVeS. Our work facilitates the reuse and extension of existing models. It also supports collaborative modelling. Finally, it contributes to better reproducibility of modelling results and to the challenge of model provenance.
Our algorithm is the first tailor-made detector of differences between versions of computational models in standard formats.
Author Comment
Our algorithm is the first tailor-made detector of differences between versions of computational models in standard formats.
Supplemental Information
S1: Model Version V1 from Figure 4
Extracted reaction R3 from BIOMD0000000107, release number 8 (June 2007) of BioModels Database.
S2: Model Version V2 from Figure 4
Extracted reaction R3 from BIOMD0000000107, release number 25 (June 2013) of BioModels Database.
S3: Unix’ diff on S1 and S2
Differences between S1 and S2 obtained by executing Unix’ diff with diff S1.xml S2.xml > S3.xml.
S4: BiVeS on S1 and S2
Differences between S1 and S2 obtained by executing BiVeS with java -jar BiVeS-fat.jar S1.xml S2.xml > S4.xml.