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The Kappa platform for rule-based modeling
MOTIVATION: We present an overview of the Kappa platform, an integrated suite of analysis and visualization techniques for building and interactively exploring rule-based models. The main components of the platform are the Kappa Simulator, the Kappa Static Analyzer and the Kappa Story Extractor. In...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6022607/ https://www.ncbi.nlm.nih.gov/pubmed/29950016 http://dx.doi.org/10.1093/bioinformatics/bty272 |
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author | Boutillier, Pierre Maasha, Mutaamba Li, Xing Medina-Abarca, Héctor F Krivine, Jean Feret, Jérôme Cristescu, Ioana Forbes, Angus G Fontana, Walter |
author_facet | Boutillier, Pierre Maasha, Mutaamba Li, Xing Medina-Abarca, Héctor F Krivine, Jean Feret, Jérôme Cristescu, Ioana Forbes, Angus G Fontana, Walter |
author_sort | Boutillier, Pierre |
collection | PubMed |
description | MOTIVATION: We present an overview of the Kappa platform, an integrated suite of analysis and visualization techniques for building and interactively exploring rule-based models. The main components of the platform are the Kappa Simulator, the Kappa Static Analyzer and the Kappa Story Extractor. In addition to these components, we describe the Kappa User Interface, which includes a range of interactive visualization tools for rule-based models needed to make sense of the complexity of biological systems. We argue that, in this approach, modeling is akin to programming and can likewise benefit from an integrated development environment. Our platform is a step in this direction. RESULTS: We discuss details about the computation and rendering of static, dynamic, and causal views of a model, which include the contact map (CM), snaphots at different resolutions, the dynamic influence network (DIN) and causal compression. We provide use cases illustrating how these concepts generate insight. Specifically, we show how the CM and snapshots provide information about systems capable of polymerization, such as Wnt signaling. A well-understood model of the KaiABC oscillator, translated into Kappa from the literature, is deployed to demonstrate the DIN and its use in understanding systems dynamics. Finally, we discuss how pathways might be discovered or recovered from a rule-based model by means of causal compression, as exemplified for early events in EGF signaling. AVAILABILITY AND IMPLEMENTATION: The Kappa platform is available via the project website at kappalanguage.org. All components of the platform are open source and freely available through the authors’ code repositories. |
format | Online Article Text |
id | pubmed-6022607 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-60226072018-07-10 The Kappa platform for rule-based modeling Boutillier, Pierre Maasha, Mutaamba Li, Xing Medina-Abarca, Héctor F Krivine, Jean Feret, Jérôme Cristescu, Ioana Forbes, Angus G Fontana, Walter Bioinformatics Ismb 2018–Intelligent Systems for Molecular Biology Proceedings MOTIVATION: We present an overview of the Kappa platform, an integrated suite of analysis and visualization techniques for building and interactively exploring rule-based models. The main components of the platform are the Kappa Simulator, the Kappa Static Analyzer and the Kappa Story Extractor. In addition to these components, we describe the Kappa User Interface, which includes a range of interactive visualization tools for rule-based models needed to make sense of the complexity of biological systems. We argue that, in this approach, modeling is akin to programming and can likewise benefit from an integrated development environment. Our platform is a step in this direction. RESULTS: We discuss details about the computation and rendering of static, dynamic, and causal views of a model, which include the contact map (CM), snaphots at different resolutions, the dynamic influence network (DIN) and causal compression. We provide use cases illustrating how these concepts generate insight. Specifically, we show how the CM and snapshots provide information about systems capable of polymerization, such as Wnt signaling. A well-understood model of the KaiABC oscillator, translated into Kappa from the literature, is deployed to demonstrate the DIN and its use in understanding systems dynamics. Finally, we discuss how pathways might be discovered or recovered from a rule-based model by means of causal compression, as exemplified for early events in EGF signaling. AVAILABILITY AND IMPLEMENTATION: The Kappa platform is available via the project website at kappalanguage.org. All components of the platform are open source and freely available through the authors’ code repositories. Oxford University Press 2018-07-01 2018-06-27 /pmc/articles/PMC6022607/ /pubmed/29950016 http://dx.doi.org/10.1093/bioinformatics/bty272 Text en © The Author(s) 2018. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Ismb 2018–Intelligent Systems for Molecular Biology Proceedings Boutillier, Pierre Maasha, Mutaamba Li, Xing Medina-Abarca, Héctor F Krivine, Jean Feret, Jérôme Cristescu, Ioana Forbes, Angus G Fontana, Walter The Kappa platform for rule-based modeling |
title | The Kappa platform for rule-based modeling |
title_full | The Kappa platform for rule-based modeling |
title_fullStr | The Kappa platform for rule-based modeling |
title_full_unstemmed | The Kappa platform for rule-based modeling |
title_short | The Kappa platform for rule-based modeling |
title_sort | kappa platform for rule-based modeling |
topic | Ismb 2018–Intelligent Systems for Molecular Biology Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6022607/ https://www.ncbi.nlm.nih.gov/pubmed/29950016 http://dx.doi.org/10.1093/bioinformatics/bty272 |
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