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

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.

[1]  C. Maranas,et al.  Improving prediction fidelity of cellular metabolism with kinetic descriptions. , 2015, Current opinion in biotechnology.

[2]  Jonathan Strutz,et al.  Metabolic kinetic modeling provides insight into complex biological questions, but hurdles remain. , 2019, Current opinion in biotechnology.

[3]  Gary D. Bader,et al.  Cytoscape.js: a graph theory library for visualisation and analysis , 2015, Bioinform..

[4]  Chris J. Myers,et al.  JSBML 1.0: providing a smorgasbord of options to encode systems biology models , 2015, Bioinform..

[5]  D. Marquardt An Algorithm for Least-Squares Estimation of Nonlinear Parameters , 1963 .

[6]  Andreas Dräger,et al.  Clinical Applications of Metabolic Models in SBML Format , 2020 .

[7]  E. Klipp,et al.  Integrative model of the response of yeast to osmotic shock , 2005, Nature Biotechnology.

[8]  Rainer Storn,et al.  Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..

[9]  Henning Hermjakob,et al.  BioModels—15 years of sharing computational models in life science , 2019, Nucleic Acids Res..

[10]  Herbert M. Sauro,et al.  SBW - A Modular Framework for Systems Biology , 2006, Proceedings of the 2006 Winter Simulation Conference.

[11]  Zhen Zhang,et al.  Evaluation of rate law approximations in bottom-up kinetic models of metabolism , 2016, BMC Systems Biology.

[12]  Kenneth Levenberg A METHOD FOR THE SOLUTION OF CERTAIN NON – LINEAR PROBLEMS IN LEAST SQUARES , 1944 .

[13]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[14]  Vincent Schächter,et al.  CycSim—an online tool for exploring and experimenting with genome-scale metabolic models , 2009, Bioinform..

[15]  Mats Jirstrand,et al.  Systems biology Systems Biology Toolbox for MATLAB : a computational platform for research in systems biology , 2006 .

[16]  Jonathan R. Karr,et al.  RunBioSimulations: an extensible web application that simulates a wide range of computational modeling frameworks, algorithms, and formats , 2021, bioRxiv.

[17]  Linda Petzold,et al.  Kinetic modeling of biological systems. , 2009, Methods in molecular biology.

[18]  Andreas Zell,et al.  SBMLSimulator: A Java Tool for Model Simulation and Parameter Estimation in Systems Biology , 2014, Comput..

[19]  Edda Klipp,et al.  The discrepancy between data for and expectations on metabolic models: How to match experiments and computational efforts to arrive at quantitative predictions? , 2018 .

[20]  Noriko Hiroi,et al.  LibSBMLSim: a reference implementation of fully functional SBML simulator , 2013, Bioinform..

[21]  James A. Glazier,et al.  libRoadRunner 2.0: a high performance SBML simulation and analysis library , 2022, Bioinformatics.

[22]  Kody M. Powell,et al.  Nonlinear modeling, estimation and predictive control in APMonitor , 2014, Comput. Chem. Eng..

[23]  Hiroaki Kitano,et al.  SBML Level 3: an extensible format for the exchange and reuse of biological models , 2020, Molecular systems biology.

[24]  Andreas Zell,et al.  Modeling metabolic networks in C . glutamicum : a comparison of rate laws in combination with various parameter optimization strategies , 2009 .

[25]  Jacky L. Snoep,et al.  Web-based kinetic modelling using JWS Online , 2004, Bioinform..

[26]  Michael Hucka,et al.  LibSBML: an API Library for SBML , 2008, Bioinform..

[27]  Mudita Singhal,et al.  COPASI - a COmplex PAthway SImulator , 2006, Bioinform..

[28]  Matthias König,et al.  The systems biology simulation core library , 2020, Bioinform..

[29]  Andreas Zell,et al.  The systems biology simulation core algorithm , 2013, BMC Systems Biology.

[30]  John A. Nelder,et al.  A Simplex Method for Function Minimization , 1965, Comput. J..