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Article

SBMLWebApp: Web-Based Simulation, Steady-State Analysis, and Parameter Estimation of Systems Biology Models

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Department of Biosciences and Informatics, Keio University, 3-14-1 Hiyoshi Kouhoku-ku, Yokohama 223-8522, Japan
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Hewlett Packard Japan, G.K. 2-2-1 Ohjima Koto-ku, Tokyo 136-0072, Japan
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Institute for Theoretical Biology, Institute of Biology, Humboldt University, 10115 Berlin, Germany
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Computational Systems Biology of Infections and Antimicrobial-Resistant Pathogens, Institute for Bioinformatics and Medical Informatics (IBMI), University of Tübingen, 72076 Tübingen, Germany
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Department of Computer Science, University of Tübingen, 72076 Tübingen, Germany
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Cluster of Excellence ‘Controlling Microbes to Fight Infections’, University of Tübingen, 72076 Tübingen, Germany
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German Center for Infection Research (DZIF), Partner Site Tübingen, 72076 Tübingen, Germany
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Author to whom correspondence should be addressed.
Academic Editor: Hector Budman
Processes 2021, 9(10), 1830; https://doi.org/10.3390/pr9101830
Received: 11 August 2021 / Revised: 5 October 2021 / Accepted: 12 October 2021 / Published: 15 October 2021
(This article belongs to the Special Issue Next-Generation Methods and Simulation Tools for Systems Biology)
In systems biology, biological phenomena are often modeled by Ordinary Differential Equations (ODEs) and distributed in the de facto standard file format SBML. The primary analyses performed with such models are dynamic simulation, steady-state analysis, and parameter estimation. These methodologies are mathematically formalized, and libraries for such analyses have been published. Several tools exist to create, simulate, or visualize models encoded in SBML. However, setting up and establishing analysis environments is a crucial hurdle for non-modelers. Therefore, easy access to perform fundamental analyses of ODE models is a significant challenge. We developed SBMLWebApp, a web-based service to execute SBML-based simulation, steady-state analysis, and parameter estimation directly in the browser without the need for any setup or prior knowledge to address this issue. SBMLWebApp visualizes the result and numerical table of each analysis and provides a download of the results. SBMLWebApp allows users to select and analyze SBML models directly from the BioModels Database. Taken together, SBMLWebApp provides barrier-free access to an SBML analysis environment for simulation, steady-state analysis, and parameter estimation for SBML models. SBMLWebApp is implemented in Java™ based on an Apache Tomcat® web server using COPASI, the Systems Biology Simulation Core Library (SBSCL), and LibSBMLSim as simulation engines. SBMLWebApp is licensed under MIT with source code freely available. At the end of this article, the Data Availability Statement gives the internet links to the two websites to find the source code and run the program online. View Full-Text
Keywords: SBML; kinetic models; time-course simulation; steady-state simulation; parameter estimation; model calibration; software; web application SBML; kinetic models; time-course simulation; steady-state simulation; parameter estimation; model calibration; software; web application
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MDPI and ACS Style

Yamada, T.G.; Ii, K.; König, M.; Feierabend, M.; Dräger, A.; Funahashi, A. SBMLWebApp: Web-Based Simulation, Steady-State Analysis, and Parameter Estimation of Systems Biology Models. Processes 2021, 9, 1830. https://doi.org/10.3390/pr9101830

AMA Style

Yamada TG, Ii K, König M, Feierabend M, Dräger A, Funahashi A. SBMLWebApp: Web-Based Simulation, Steady-State Analysis, and Parameter Estimation of Systems Biology Models. Processes. 2021; 9(10):1830. https://doi.org/10.3390/pr9101830

Chicago/Turabian Style

Yamada, Takahiro G., Kaito Ii, Matthias König, Martina Feierabend, Andreas Dräger, and Akira Funahashi. 2021. "SBMLWebApp: Web-Based Simulation, Steady-State Analysis, and Parameter Estimation of Systems Biology Models" Processes 9, no. 10: 1830. https://doi.org/10.3390/pr9101830

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