RANGE (RAndom Network GEnerator) and the NEMO (NEtwork MOtif) language
Download ver 1.4 (2008-01-22)
ver 1.4 produces a "fat-tail" distribution, whose higher degree nodes follow a power-law. Future versions of RANGE will attempt to include all nodes in the power-law.
News: A paper on RANGE and NEMO has been accepted, Bioinformatics 2008 Jan 1;24(1):132-4. Epub 2007 Nov 3.
RANGE will generate large random transcription networks, with up to
16,000 genes, in the NEMO language.
NEMO's compiler (nemo2sbml) uses lex and yacc to output a Systems Biology
Markup Language (SBML) model for either user-specified and/or randomized gene
input functions. The randomized gene input functions are Generalized Hill
Functions with non-linear terms representing interaction between transcription
factors, whose parameters are randomly picked. The SBML model of the known
network may be input to a biochemical simulator (i.e. COPASI), allowing the
generation of synthetic microarray data for algorithm development purposes. A
script in the R language adds noise to the synthetic data.
Alternately, NEMO may be used by itself to simply describe and SBML-ize your
existing biochemical network. NEMO has language constructs for network motifs
as categorized in:
An Introduction to Systems Biology: Design Principles of Biological Circuits
by Uri Alon, Chapman & Hall/CRC; 1st edition (July 7, 2006)
Future feature: The current default behavior is that all transcription factors are active. In order to simulate different behavior for a network, NEMO will be extended to simulate the allosteric effects of signal transduction so that groups of transcription factors may be turned on and off.
Networks may be visualized in cytoscape by passing a -x flag to nemo2sbml,
which outputs an XGMML file in addition to the SBML file.
Example networks:
A 100 gene network in XGMML produced by RANGE/NEMO.
A 1000 gene network in XGMML produced by RANGE/NEMO.
Example expression output for 75 genes from a 500 node network generated by RANGE.
The compiled network was run through the COPASI biochemical simulator.
James Long
Biotechnology Computing Research Group
University of Alaska Fairbanks
PO Box 757000
Fairbanks, AK 99775-7000
USA
Voice: (907) 474-5769
jlong@alaska.edu
Biotechnology Computing Research Group