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

Takahiro G Yamada,Matthias König,Martina Feierabend,Andreas Dräger,Kaito Ii,Akira Funahashi

doi:10.3390/pr9101830

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™ 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.

Highlights

An enormous intrinsic complexity characterizes biological systems from their smallest independently functioning unit, the individual cell, to entire organ systems and beyond.This complexity can be attributed to emergent characteristics of the individual components of biological systems and their interactions [1]
The present study focuses on kinetic models
The SBMLWebApp supports interdisciplinary collaboration as it allows experimentalists to effortlessly try out in-silico models from their dry-lab collaborators, which may help to accelerate the iterative cycles of alternating model development and wet-lab experimentation towards scientific progress

Summary

Introduction

An enormous intrinsic complexity characterizes biological systems from their smallest independently functioning unit, the individual cell, to entire organ systems and beyond. This article presents the user-friendly web application SBMLWebApp which allows the integrated analysis of kinetic models using time-course simulation, steady-state analysis, and parameter estimation. Providing a directly accessible web application with an intuitive user interface that combines services for time-course simulation, steady-state analysis, and parameter estimation makes a large portion of typical analyses within systems biology research accessible to less experienced users. In this way, the SBMLWebApp supports interdisciplinary collaboration as it allows experimentalists to effortlessly try out in-silico models from their dry-lab collaborators, which may help to accelerate the iterative cycles of alternating model development and wet-lab experimentation towards scientific progress

Implementation

Using the SBMLWebApp

Real-World Example and Applications

Limitations of the Application

Conclusions