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Example: Structural Analysis of a Network Generated by the Charleston-Ho Model
A screenshot of the console of a sample run
In this example, a computational pipeline is constructed to understand the topology of a network generated by the
Charleston-Ho model. A Perl script is written for this purpose (the sample script is packaged with the GNLab distribution).
In this exemplary study, a 100-node network is generated using the Charleston-Ho model. The network
is visualized using GraphViz, and its topological features are extracted in GNLab. The results
are shown below.
Visualization of the generated 100-node network.
A file containing the topological features of the 100-node network. The distributions of the
node in- and out- degree are also shown.
Application: Evaluation of GRN Inference Methods
Schematic diagram of an evaluation framework for the reliability of GRN inference methods
A computational framework for GRN inference evaluation can be constructed using GNLab. In such
a framework, a random network is generated then simulated to obtain a set of microarray data. The
simulated data can then be used to infer a network using a GRN inference method. The similarity between
the inferred and the original networks provides a quantitative measure of inference reliability
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