Category Cross-Omics>Pathway Analysis/Gene Regulatory Networks/Tools

Abstract SimBoolNet is an open source Cytoscape plug-in that simulates the dynamics of signaling transduction using Boolean networks.

Given a user-specified level of stimulation to signal receptors, SimBoolNet simulates the response of downstream molecules and visualizes with animation and records the dynamic changes of the network.

It can be used to generate hypotheses and facilitate experimental studies about causal relations and crosstalk among cellular signaling pathways.

SimBoolNet is based on an extended Boolean network model (see below...), in which the state of each node is a variable between 0 and 1 representing the probability (or percentage) of activation and each edge (representing activation or repression) has associated with it a weight representing efficiency of propagating the corresponding signal.

Boolean networks --

A Boolean network is a directed graph in which the nodes represent elements (e.g. genes, proteins) in the network and the edges represent interactions (e.g. gene regulation, phosphorylation) between two types of elements.

Every node is assigned a state of ON/OFF, and at each time point the state of a node is determined by the states of its upstream neighbors via a transfer logical function.

Recently, it was shown that simple models combining Boolean networks with ‘fuzzy logic’ can capture most features of the signaling data.

SimBoolNet as a Java plug-in for Cytoscape --

As a Java plug-in for Cytoscape (see G6G Abstract Number 20092), an open source framework for analyzing biological networks, SimBoolNet allows users to take advantage of the advanced functionalities and friendly graphic user interface of Cytoscape.

Given the user-specified levels of stimulation to a signaling network, SimBoolNet simulates the response of downstream molecules, which can be visualized with animations and recorded for further analyses.

Despite its simplicity, SimBoolNet was able to capture the general trends in signaling networks and recapitulate experimental results in the manufacturer's previous study of crosstalk among three (3) signaling pathways (Zielinski R, et al. - The crosstalk between EGF, IGF, and insulin cell signaling pathways - computational and experimental analysis. BMC Syst. Biol. (2009).

SimBoolNet is a useful tool for exploratory analysis of a signaling network, e.g. hypothesizing causal relation and crosstalks among signaling molecules, elucidating mechanisms behind signaling abnormalities in diseases, etc.

SimBoolNet provides both single and batch running modes --

In single mode, users can specify the input activity (e.g. percentages of phosphorylation) of signal receptors. The activities of nodes will change step by step according to the provided algorithm. This process is visualized both by the dynamic change of node colors from gray (less active) to red (active).

A batch-mode run consists of multiple single-mode runs, each with a different combination of activities of input nodes.

Using JFreeChart (see below...), SimBoolNet draws the time series of node changes in a single-mode simulation, and a scatter plot with a regression line between an input node and a downstream node in a batch-mode simulation.

All configurations of the simulation model and its results can be exported to a hard disk for further analysis.

JFreeChart --

JFreeChart is a free 100% Java chart library that makes it easy for developers to display professional quality charts in their applications. JFreeChart's feature set includes:

1) A consistent and well-documented Application Programming Interface (API), supporting a wide range of chart types;

2) A flexible design that is easy to extend, and targets both server-side and client-side applications;

3) Support for many output types, including Swing components, image files (including PNG and JPEG), and vector graphics file formats (including PDF, EPS and SVG); and

4) JFreeChart is “open source” or, more specifically, free software. It is distributed under the terms of the GNU Lesser General Public License (LGPL), which permits use in proprietary applications.

SimBoolNet Use Case --

In the manufacturers recent work (Zielinski et al., 2009); the manufacturer used SimBoolNet to study the crosstalk in a combined signaling network of three (3) cancer-related signaling pathways: epidermal growth factor receptor, insulin-like growth factor-1 receptor and insulin receptor.

The manufacturer first predicted the response of the output molecules using SimBoolNet, and then carried out real experiments to measure the phosphorylation levels of the selected molecules in SKOV3 (human ovary carcinoma) cells.

Most of the trends suggested by the SimBoolNet simulation have been confirmed by the experimental studies.

Allowing for dynamic visualization and interactive analysis of simulated states of the network, SimBoolNet provided valuable insight about the mechanism of crosstalk between the three (3) signaling pathways.

SimBoolNet Documentation --

The manufacturer provides an above average User Manual in the PDF format.

System Requirements

Contact manufacturer.


Manufacturer Web Site SimBoolNet

Price Contact manufacturer.

G6G Abstract Number 20613

G6G Manufacturer Number 104214