1. Introduction
Cellware has been designed to model whole cell biochemical reactions. Besides the capabilities of simulating biochemical pathways that consist of gene regulation networks and metabolic pathways, Cellware also includes analysis tools like parameter estimation and graph layout algorithms.

Cellware uses a proprietary file format (CWM or Cellware model) that stores information pertaining to the model and the corresponding simulation environment in Cellware. Cellware supports import and export of models from the System Biology Mark-up Language (SBML) file format.

The following is a summary of the functionality of Cellware:

  • Grid Enabled
    Computational needs of large models can be met by distributing it seamlessly to a Grid environment.

  • Multi-platform
    Cellware is a multi-platform software that has been developed in Java. The Grid version implements the front-end in Java and back-end in C++. It has been tested on Windows, Linux/Unix and Macintosh platforms.


  • Biologist-friendly User Interface (UI)
    The user interface has been designed to be as friendly as possible for the biologist. The UI provides adequate tools for cell model building while abstracting certain underlying mechanism from the users.


  • Extensive Coverage of Algorithms Library for Quantitative Simulation
    Cellware comes with comprehensive libraries ranging from determinism to stochasticity. It also incorporates parameter estimation modules based on SWARM algorithms.


  • Network Analysis
    Cellware is able to provide users the network statistics for the models, which are being loaded. In addition, finding conserved pathways between pathways is another main function in analysis.


This tutorial will guide the users through Cellware by introducing various features and functions in greater details.

Chapter 2 describes how to download and install Cellware. The existing Cellware users may skip to Chapter 3 directly.

Chapter 4 highlights all details with regards to the GUI and introduces users to various functionality of Cellware.

How to access the pathway database (KEGG) is depicted in Chapter 5.

In Chapter 6 biologically relevant examples are presented, which provides step-by-step guide to construction of models using Cellware.

Lastly Chapter 7 that explains architecture and the algorithms library of Cellware.