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Introduction

Since a few years, large scale biological studies produced huge amounts of data about networks of molecular interactions (protein interactions, gene regulation, metabolic reactions, signal transduction). The integration of these data sets can be combined to acquire a global view of the pieces that, altogether, contribute to the complexity of biological processes. High-throughput data is however notoriously noisy and incomplete, and it is important to evaluate the quality of the different pieces of information that are taken in consideration for building higher views of biological networks.

An important effort will be required to extract reliable information from the ever-increasing ocean of high-throughput data. This will require the utilization of powerful tools that enable us to apply statistical analysis on large graphs. For this purpose, we developed the Network Analysis Tools (NeAT), as set of tools performing basic operations on networks and clusters.

The tools can be used in three ways:

  1. Web server interface

    http://rsat.scmbb.ulb.ac.be/neat/

    The Web interface gives a convenient and intuitive access to the tools, and allows you to bring your data sets through some typical analysis work flows in order to extract the best of it.

  2. Stand-alone application

    http://rsat.scmbb.ulb.ac.be/rsat/distrib/

    Most of the tools are freely available to academic users, according to a licence for non-commercial and non-military usage.

    The license covers both the Regulatory Sequence Analysis Tools (RSAT) and the Network Analysis Tools (NeAT). It can be downloaded from the RSAT Web site.

  3. Web services

    In addition, people having computer skills can also use be same tools via a Web services interface, in order to integrate them in automatic work-flows. To obtain information on the Web services, connect the NeATweb server, and in the left menu, select Information - Web services.


next up previous contents
Next: Network visualization and format Up: Network Analysis Tools (NeAT) Previous: Contents   Contents
RSAT 2009-09-04