Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

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

Version 1 : Received: 11 August 2021 / Approved: 11 August 2021 / Online: 11 August 2021 (12:19:38 CEST)

A peer-reviewed article of this Preprint also exists.

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. 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.

Journal reference: Processes 2021, 9, 1830
DOI: 10.3390/pr9101830

Abstract

In systems biology, biological phenomena are often modeled by ODE 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 simulations, 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 SBSCL, and LibSBMLSim as simulation engines. SBMLWebApp is licensed under MIT with source code available from https://github.com/TakahiroYamada/SBMLWebApp. The program runs online at http://simulate-biology.org.

Keywords

SBML; kinetic models; time-course simulation; steady-state simulation; parameter estimation; model calibration; software; web application

Subject

LIFE SCIENCES, Other

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