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GSOC2017 Web App for SBML Model Analysis



In systems biology, it is very important to standardize the model for a given biological phenomenon and analyze the system based on this model. Such a model is most of the time based on ordinary differential equation (ODE).

Such a systems biology model is normally described in a standard format, with Systems Biology Markup Language (SBML) being the de-facto standard in the field. Several software tools exist to create SBML models easily. Regarding the analysis of such models, which is mainly via simulation, steady state analysis, or parameter estimation.

  • Time course simulation provides the information of each species in the model over time which enables us to understand the dynamical variation of species in model.

  • Steady state analysis can give us the values of model objects after enough time has passed and a steady state is reached.

  • Parameter estimation focuses on the identification of unknown parameters in the model based on experimental data.

Time course simulation, steady state simulation and parameter estimation are implemented in multiple libraries and tools for SBML, e.g. COPASI, libroadrunner, or the Simulation Core Library. However, establishing the environment for such analysis is often difficult for biologists and a major obstacle to analyze ODE models easily.

Project goals

GSOC 2017 This project is part of Google Summer of Code 2017 with the goal of developing a Web App for SBML models which provides functionality for

  • time course simulation
  • steady state analysis
  • parameter estimation

The Web App will provide options for uploading SBML models and experimental data files and run the respective simulations with the models.

Repository Content

This repository includes the following files and directories

  • docs/ SBML example files for analysis
  • examples/ SBML example files for analysis
  • lib/ Library dependencies
  • src/ Source code for web app
  • WebContent/ Web content for web app
  • Overview information
  • pom.xml Maven pom file

Additional information



This project is created in Java as a Maven project. To run the web app locally one can run the server from within eclipse.

Tomcat download

Apache tomcat is not contained in the installation, but must be installed separately. During the development Apache TomCat v6.0.48 is used which is available as apache-tomcat-6.0.48.tar.gz from

After download the files should be unpacked in the correct position (e.g. :/Applications/).


Eclipse tomcat plugin installation

When you use Eclipse , eclipse tomcat plugin is needed. This file can be downloaded following Task.

  1. Select Help - Eclipse Marketplace
  2. Type "tomcat" in find text box
  3. Install "Eclipse Tomcat Plugin 9.1.2"

Then you start-up eclipse. When you can see the icon of tomcat in Eclipse , the install is accomplished.

Tomcat installation in Eclipse

After you complete installation of eclipse tomcat plugin, you should choose the tomcat version and tomcat home from Environment -> Tomcat. For version, please check version 6.x and select the aforementioned distribution of apache-tomcat-6.0.48.

Run Server

After finishing the tomcat configuration one can run the server in Eclipse via:

  1. Clone repository git clone
  2. Select File -> Open Projects from File System
  3. Choose the directory of this project in Import source
  4. Select Properties -> Java Build Path -> Libraries - add library - Server Runtime - Apache Tomcat v6.0

Jetbrains idea

  • Run | Edit Configurations | + | Tomcat Server | Local
  • Select tomcat: Configure -> Select apache-tomcat-6.0.48
  • Select artifact to deploy: Artifact GSOC_WebMavenProject:war
  • Add external libraries to java.library.path in VM options i.e.

see also

Docker Image

Docker Image of this application has been already prepared. If you felt annoying when you use this application via our server, installing this image and create the container based on it and executing analysis is better for you.

Docker installation :

  1. docker pull takahiroyamada/gsoc_sbmlanalysis
  2. docker run -it --rm -p 80:8080 takahiroyamada/gsoc_sbmlanalysis

Then you can execute analysis using your favorite browser with the URL of "http://localhost/GSOC_WebMavenProject-0.0.1-SNAPSHOT/"


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