Network Motif Identification in Stochastic Networks

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Details:

This program is intended to implement the methodology for network motif identification in stochastic networks. The details of the methodology as well as the correct citation for this program are as follows: Rui Jiang, Zhidong Tu, Ting Chen, and Fengzhu Sun. Proc. Natl. Acad. Sci. USA, Vol.103, No.25, 9404~9409, 2006. This program is written in C++ and can be compiled using standard compilers. Furthermore, each step of the program is well documented.

Code and Executables:

Pre-compiled executables: 

• Linux OS: emnm_linux.tar.gz(64-bit)
• Unix OS:
• Windows OS: emnm_windows.zip(32-bit)
• Mac OS:

readme file (PDF format):
Contains information about the running environment of the program.

Sample Data Sets:

Sample input file of a yeast regulatory network composed of 688 nodes and 1077 edges:

• node.txt - contains node information of the yeast regulatory network.
• edge.txt - contains edge information of the yeast regulatory network.

Results:  

Sample output files:

• subnumb.03.txt - numbers of 3-node subgraphs in the original yeast regulatory network.
• simunumb.03.txt - expected numbers of 3-node subgraphs in the randomized networks.
• simuprob.03.txt - probabilities of observing the 3-node subgraphs in the randomized networks.
• emsimu.03c.txt - stochastic network motifs identified in the yearst regulatory network.

Please contact us if there are any bugs within our program. 
Copyright © 2006 The University of Southern California. All RIGHTS RESERVED.

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Created Date: October 2006
Last Updated Date: October 31, 2006
Contact

Fengzhu Sun, Ph.D.
 Molecular and Computational Biology Program
 Department of Biological Sciences
 University of Southern California
 Los Angeles, CA, 90089
 (213) 740-2413 (phone)
 (213) 740-2424 (fax)
 Email: fsun AT usc DOT edu