This Article 
 Bibliographic References 
 Add to: 
SimBioNeT: A Simulator of Biological Network Topology
March/April 2012 (vol. 9 no. 2)
pp. 592-600
Barbara Di Camillo, University of Padova, Padova
Marco Falda, University of Padova, Padova
Gianna Toffolo, University of Padova, Padova
Claudio Cobelli, University of Padova, Padova
Studying biological networks at topological level is a major issue in computational biology studies and simulation is often used in this context, either to assess reverse engineering algorithms or to investigate how topological properties depend on network parameters. In both contexts, it is desirable for a topology simulator to reproduce the current knowledge on biological networks, to be able to generate a number of networks with the same properties and to be flexible with respect to the possibility to mimic networks of different organisms. We propose a biological network topology simulator, SimBioNeT, in which module structures of different type and size are replicated at different level of network organization and interconnected, so to obtain the desired degree distribution, e.g., scale free, and a clustering coefficient constant with the number of nodes in the network, a typical characteristic of biological networks. Empirical assessment of the ability of the simulator to reproduce characteristic properties of biological network and comparison with E. coli and S. cerevisiae transcriptional networks demonstrates the effectiveness of our proposal.

[1] Z.N. Oltvai and A.L. Barabasi, “Systems Biology. Life's Complexity Pyramid,” Science, vol. 298, pp. 763-764, Oct. 2002.
[2] N. Przulj, D.A. Wigle, and I. Jurisica, “Functional Topology in a Network of Protein Interactions,” Bioinformatics, vol. 20, pp. 340-348, Feb. 2004.
[3] E. Almaas, B. Kovacs, T. Vicsek, Z.N. Oltvai, and A.L. Barabasi, “Global Organization of Metabolic Fluxes in the Bacterium Escherichia Coli,” Nature, vol. 427, pp. 839-843, Feb. 2004.
[4] L.G. Alexopoulos, J. Saez-Rodriguez, B.D. Cosgrove, D.A. Lauffenburger, and P.K. Sorger, “Networks Inferred from Biochemical Data Reveal Profound Differences in Toll-Like Receptor and Inflammatory Signaling between Normal and Transformed Hepatocytes,” Molecular and Cellular Proteomics, vol. 9, no. 9, pp. 1849-65, 2010.
[5] D. Di Bernardo, T.S. Gardnerand, and J.J. Collins, “Robust Identification of Large Genetic Networks,” Proc. Pacific Symp. Biocomputing, pp. 486-497, 2004.
[6] N. Soranzo, G. Bianconiand, and C. Altafini, “Comparing Association Network Algorithms for Reverse Engineering of Large-Scale Gene Regulatory Networks: Synthetic Versus Real Data,” Bioinformatics, vol. 23, pp. 1640-1647, July 2007.
[7] P. Mendes, W. Shaand, and K. Ye, “Artificial Gene Networks for Objective Comparison of Analysis Algorithms,” Bioinformatics, vol. 19, no. 2, pp. 122-129, Oct. 2003.
[8] T. Van den Bulcke, K. Van Leemput, B. Naudts, P. van Remortel, H. Ma, A. Verschoren, B. De Moor, and K. Marchal, “SynTReN: A Generator of Synthetic Gene Expression Data for Design and Analysis of Structure Learning Algorithms,” BMC Bioinformatics, vol. 7, article 43, Jan. 2006.
[9] P. Gennemark and D. Wedelin, “Benchmarks for Identification of Ordinary Differential Equations from Time Series Data,” Bioinformatics, vol. 25, pp. 780-786, Mar. 2009.
[10] H. Hache, C. Wierling, H. Lehrachand, and R. Herwig, “GeNGe: Systematic Generation of Gene Regulatory Networks,” Bioinformatics, vol. 25, pp. 1205-1207, May 2009.
[11] D. Marbach, T. Schaffter, C. Mattiussi, and D. Floreano, “Generating Realistic in Silico Gene Networks for Performance Assessment of Reverse Engineering Methods,” J. Computational Biology : A J. Computational Molecular Cell Biology, vol. 16, pp. 229-239, Feb. 2009.
[12] V.A. Smith, E.D. Jarvisand, and A.J. Hartemink, “Evaluating Functional Network Inference Using Simulations of Complex Biological Systems,” Bioinformatics, vol. 18 Suppl 1, pp. S216-S224, 2002.
[13] B. Di Camillo, G. Toffolo, and C. Cobelli, “A Gene Network Simulator to Assess Reverse Engineering Algorithms,” Annals of the New York Academy of Sciences, vol. 1158, pp. 125-142, Mar. 2009.
[14] R. Milo, S. Shen-Orr, S. Itzkovitz, N. Kashtan, D. Chklovskii, and U. Alon, “Network Motifs: Simple Building Blocks of Complex Networks,” Science, vol. 298, pp. 824-827, Oct. 2002.
[15] R. Milo, S. Itzkovitz, N. Kashtan, R. Levitt, S. Shen-Orr, I. Ayzenshtat, M. Sheffer, and U. Alon, “Superfamilies of Evolved and Designed Networks,” Science, vol. 303, pp. 1538-1542, Mar. 2004.
[16] S.A. Kauffman, “Metabolic Stability and Epigenesis in Randomly Constructed Genetic Nets,” J. Theoretical Biology, vol. 22, pp. 437-467, Mar. 1969.
[17] A. Wagner, “Does Evolutionary Plasticity Evolve?,” Evolution, vol. 50, pp. 1008-1023, 1996.
[18] A.L. Barabasi and R. Albert, “Emergence of Scaling in Random Networks,” Science, vol. 286, pp. 509-512, Oct. 1999.
[19] A.L. Barabasi and E. Bonabeau, “Scale-Free Networks,” Scientific Am., vol. 288, pp. 60-69, May 2003.
[20] H. Jeong, S.P. Mason, A.L. Barabasiand, and Z.N. Oltvai, “Lethality and Centrality in Protein Networks,” Nature, vol. 411, pp. 41-42, May 2001.
[21] M.M. Babu, N.M. Luscombe, L. Aravind, M. Gerstein, and S.A. Teichmann, “Structure and Evolution of Transcriptional Regulatory Networks,” Current Opinion in Structural Biology, vol. 14, pp. 283-291, June 2004.
[22] D.J. Watts and S.H. Strogatz, “Collective Dynamics of ‘Small-World’ Networks,” Nature, vol. 393, pp. 440-442, June 1998.
[23] E. Ravasz, A.L. Somera, D.A. Mongru, Z.N. Oltvai, and A.L. Barabasi, “Hierarchical Organization of Modularity in Metabolic Networks,” Science, vol. 297, pp. 1551-1555, Aug. 2002.
[24] R. Albert and A.L. Barabasi, “Statistical Mechanics of Complex Networks,” Rev. Modern Physics, vol. 74, p. 47, 2002.
[25] A.L. Barabasi and Z.N. Oltvai, “Network Biology: Understanding the Cell's Functional Organization,” Nature Rev. Genetics, vol. 5, pp. 101-113, Feb. 2004.
[26] H. Jeong, B. Tombor, R. Albert, Z.N. Oltvai, and A.L. Barabasi, “The Large-Scale Organization of Metabolic Networks,” Nature, vol. 407, pp. 651-654, Oct. 2000.
[27] A. Wagner and D.A. Fell, “The Small World Inside Large Metabolic Networks,” Proc. The Royal Soc. B: Biological Sciences, vol. 268, pp. 1803-1810, Sept. 2001.
[28] L.C. Freeman, “A Set of Measures of Centrality Based on Betweenness,” Sociometry, vol. 40, pp. 35-41, 1977.
[29] A. Arenas, A. Cabrales, A. Díaz-Guilera, R. Guimerà, and F. Vega-Redondo, “Search and Congestion in Complex Networks,” Lecture Notes in Physics, Statistical Mechanics of Complex Networks, XVIII Sitges Conf. Statistical Mechanics, vol. 625, pp. 175-194, 2003.
[30] P. Erdős and A. Rényi, “On Random Graphs. I,” Publicationes Mathematicae, vol. 6, pp. 290-297, 1959.
[31] S.S. Shen-Orr, R. Milo, S. Mangan, and U. Alon, “Network Motifs in the Transcriptional Regulation Network of Escherichia Coli,” Nature Genetics, vol. 31, pp. 64-68, 2002.

Index Terms:
Biological networks, topological properties, simulation.
Barbara Di Camillo, Marco Falda, Gianna Toffolo, Claudio Cobelli, "SimBioNeT: A Simulator of Biological Network Topology," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 9, no. 2, pp. 592-600, March-April 2012, doi:10.1109/TCBB.2011.116
Usage of this product signifies your acceptance of the Terms of Use.