SiDeS was developed by
M. Koyuturk,
A. Grama, and
W. Szpankowski at the
Parallel and Distributed Systems Lab
of the Computer Science Department at
Purdue University. It is based on
the RECOMB 2006 paper "Assessing significance of connectivity and
conservation in protein interaction networks" by Mehmet Koyuturk,
Ananth Grama and Wojciech Szpankowski, which is on the statistical
analysis of the behavior of subgraph density in large networks [1].
SiDeS implements the HCS algorithm [2], which is
modified to incorporate the above-mentioned statistical results in
evaluating the adequacy of the density of a subgraph to be considered
a "cluster". The basic building block of this heuristics is
a simple min-cut algorithm [3]. Implementation of the
Cytoscape [4] plug-in, particularly the user interface,
is based on the implementation of the
MCODE
[5] plug-in, which also targets identification of
dense subgraphs in biological networks, and is also publicly
available.
References
[1] M. Koyuturk, A. Grama, and W. Szpankowski,
Assessing significance of connectivity and conservation in protein
interaction networks. In A. Apostolico et al. (Eds.): 10th
International Conference on Research in Computational Molecular
Biology (RECOMB'06), LNBI 3909, pp. 45-59, 2006.
[2] E. Hartuv and R. Shamir. A clustering algorithm based on
graph connectivity. Information Processing Letters, 76:171.181,
2000.
[3] M. Stoer and F. Wagner. A simple min-cut algorithm. Journal
of ACM, 44(4):585.591, 1997.
[4] P. Shannon, A. Markiel, O. Ozier, N. S. Baliga, J. T. Wang,
D. Ramage, N. Amin, B. Schwikowski, and T. Ideker. Cytoscape: A
software environment for integrated models of biomolecular
interaction networks. Genome Research, 13(11):2498-504,
2003.
[5] G. D. Bader and C. W. V. Hogue. An automated method for finding
molecular complexes in large protein interaction networks. BMC
Bioinformatics, 4(2), 2003.
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