@article{Yamada2021,
  author         = {Yamada, Takahiro G. and Ii, Kaito and K\"onig, Matthias and Feierabend,
    Martina and Dr\"ager, Andreas and Funahashi, Akira},
  title          = {{SBMLWebApp: Web-Based Simulation, Steady-State Analysis, and Parameter
    Estimation of Systems Biology Models}},
  journal        = {Processes},
  volume         = {9},
  year           = {2021},
  month          = oct,
  number         = {10},
  article-number = {1830},
  url            = {https://www.mdpi.com/2227-9717/9/10/1830},
  issn           = {2227-9717},
  doi            = {10.3390/pr9101830},
  keywords       = {SBML; kinetic models; time-course simulation; steady-state simulation; parameter
    estimation; model calibration; software; web application},
  abstract       = {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\texttrademark{} based on an Apache Tomcat\textsuperscript{\textregistered} 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.},
}