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Exploring the evolution of biochemical models at the network level

The evolution of biochemical models is difficult to track. At present, it is not possible to inspect the differences between model versions at the network level. Biochemical models are often constructed in a distributed, non-linear process: collaborators create model versions on different branches f...

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Autores principales: Gebhardt, Tom, Touré, Vasundra, Waltemath, Dagmar, Wolkenhauer, Olaf, Scharm, Martin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8936491/
https://www.ncbi.nlm.nih.gov/pubmed/35312734
http://dx.doi.org/10.1371/journal.pone.0265735
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author Gebhardt, Tom
Touré, Vasundra
Waltemath, Dagmar
Wolkenhauer, Olaf
Scharm, Martin
author_facet Gebhardt, Tom
Touré, Vasundra
Waltemath, Dagmar
Wolkenhauer, Olaf
Scharm, Martin
author_sort Gebhardt, Tom
collection PubMed
description The evolution of biochemical models is difficult to track. At present, it is not possible to inspect the differences between model versions at the network level. Biochemical models are often constructed in a distributed, non-linear process: collaborators create model versions on different branches from novel information, model extensions, during curation and adaption. To discuss and align the versions, it is helpful to abstract the changes to the network level. The differences between two model versions can be detected by the software tool BiVeS. However, it cannot show the structural changes resulting from the differences. Here, we present a method to visualise the differences between model versions effectively. We developed a JSON schema to communicate the differences at the network level and extended BiVeS accordingly. Additionally, we developed DiVil, a web-based tool to represent the model and the differences as a standardised network using D3. It combines an automatic layout with an interactive user interface to improve the visualisation and to inspect the model. The network can be exported in standardised formats as images or markup language. Our method communicates the structural differences between model versions. It facilitates the discussion of changes and thus supports the collaborative and non-linear nature of model development. Availability and implementation: DiVil prototype: https://divil.bio.informatik.uni-rostock.de, Code on GitHub: https://github.com/Gebbi8/DiVil, licensed under Apache License 2.0. Contact: url="tom.gebhardt@uni-rostock.de.
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spelling pubmed-89364912022-03-22 Exploring the evolution of biochemical models at the network level Gebhardt, Tom Touré, Vasundra Waltemath, Dagmar Wolkenhauer, Olaf Scharm, Martin PLoS One Research Article The evolution of biochemical models is difficult to track. At present, it is not possible to inspect the differences between model versions at the network level. Biochemical models are often constructed in a distributed, non-linear process: collaborators create model versions on different branches from novel information, model extensions, during curation and adaption. To discuss and align the versions, it is helpful to abstract the changes to the network level. The differences between two model versions can be detected by the software tool BiVeS. However, it cannot show the structural changes resulting from the differences. Here, we present a method to visualise the differences between model versions effectively. We developed a JSON schema to communicate the differences at the network level and extended BiVeS accordingly. Additionally, we developed DiVil, a web-based tool to represent the model and the differences as a standardised network using D3. It combines an automatic layout with an interactive user interface to improve the visualisation and to inspect the model. The network can be exported in standardised formats as images or markup language. Our method communicates the structural differences between model versions. It facilitates the discussion of changes and thus supports the collaborative and non-linear nature of model development. Availability and implementation: DiVil prototype: https://divil.bio.informatik.uni-rostock.de, Code on GitHub: https://github.com/Gebbi8/DiVil, licensed under Apache License 2.0. Contact: url="tom.gebhardt@uni-rostock.de. Public Library of Science 2022-03-21 /pmc/articles/PMC8936491/ /pubmed/35312734 http://dx.doi.org/10.1371/journal.pone.0265735 Text en © 2022 Gebhardt et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Gebhardt, Tom
Touré, Vasundra
Waltemath, Dagmar
Wolkenhauer, Olaf
Scharm, Martin
Exploring the evolution of biochemical models at the network level
title Exploring the evolution of biochemical models at the network level
title_full Exploring the evolution of biochemical models at the network level
title_fullStr Exploring the evolution of biochemical models at the network level
title_full_unstemmed Exploring the evolution of biochemical models at the network level
title_short Exploring the evolution of biochemical models at the network level
title_sort exploring the evolution of biochemical models at the network level
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8936491/
https://www.ncbi.nlm.nih.gov/pubmed/35312734
http://dx.doi.org/10.1371/journal.pone.0265735
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