ArticleBioinformatics (Oxford, England)2018
The Kappa platform for rule-based modeling.
Article in Bioinformatics (Oxford, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
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Who cites it
36 citing papers in PubMed.
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- A dynamical perspective: moving towards mechanism in single-cell transcriptomics.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Review
- Enzyme-Free Exponential Amplification via Growth and Scission of Crisscross Ribbons from Single-Stranded DNA Components.Journal of the American Chemical Society · 2024Article
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- Mechanistic model of MAPK signaling reveals how allostery and rewiring contribute to drug resistance.Molecular systems biology · 2023Article
- A Practical Guide for the Efficient Formulation and Calibration of Large, Energy- and Rule-Based Models of Cellular Signal Transduction.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Compositional modelling of immune response and virus transmission dynamics.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2022Article
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- A scalable, open-source implementation of a large-scale mechanistic model for single cell proliferation and death signaling.Nature communications · 2022Article
- Probabilistic Inference with Polymerizing Biochemical Circuits.Entropy (Basel, Switzerland) · 2022Article
- Data-driven learning how oncogenic gene expression locally alters heterocellular networks.Nature communications · 2022Article
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- Validation Through Collaboration: Encouraging Team Efforts to Ensure Internal and External Validity of Computational Models of Biochemical Pathways.Neuroinformatics · 2022Review
- Comparison of rule- and ordinary differential equation-based dynamic model of DARPP-32 signalling network.PeerJ · 2022Article
- Programmatic modeling for biological systems.Current opinion in systems biology · 2021Article
- Relating simulation studies by provenance-Developing a family of Wnt signaling models.PLoS computational biology · 2021Article
- Atlas: automatic modeling of regulation of bacterial gene expression and metabolism using rule-based languages.Bioinformatics (Oxford, England) · 2021Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.