Abstract
An essential idea in the area of Systems Biology is that a good understanding of interactions between components is crucial for developing deep knowledge of the functioning of the system as a whole. Network analysis is an approach uniquely suited to uncover patterns and organizing principles in a wide variety of complex systems. In this chapter, we will give a detailed description of central network concepts and their algorithmic implementation, and demonstrate how they may be applied on two biological networks: the protein-interaction network of Mus musculus and the reconstructed genome-scale metabolic network of the bacterium Yersinia pestis.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Kitano H (2002) Systems biology: a brief overview. Science 295:1662–1664
Ideker T, Galitski T, Hood L (2001) A new approach to decoding life: systems biology. Annu Rev Genom Hum G 2:343–372
Bruggeman FJ, Westerhoff HV (2007) The nature of systems biology. Trends Microbiol 15:45–50
Barabasi AL, Oltvai ZN (2004) Network biology: understanding the cell’s functional organization. Nat Rev Genet 5:101–113
Almaas E (2007) Biological impacts and context of network theory. J Exp Biol 210:1548–1558
Albert R, Barabasi AL (2002) Statistical mechanics of complex networks. Rev Mod Phys 74:47–97
Dorogovtsev SN, Mendes JFF (2002) Evolution of networks. Adv Phys 51:1079–1187
Newman MEJ (2003) The structure and function of complex networks. Siam Rev 45:167–256
Erdős P, Rényi A (1959) On random graphs I. Publ Math 6:290–297
Barabasi AL, Albert R (1999) Emergence of scaling in random networks. Science 286:509–512
Molloy M, Reed B (1995) A critical-point for random graphs with a given degree sequence. Random Struct Algor 6:161–179
Newman MEJ, Strogatz SH, Watts DJ (2001) Random graphs with arbitrary degree distributions and their applications. Phys Rev E 64(2):026118
Vazquez A, Flammini A, Maritan A, Vespignani A (2003) Modeling of protein interaction networks. Complexus 1:38–44
Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13:2498–2504
Batagelj V, Mrvar A (2002) Pajek—analysis and visualization of large networks. Graph Drawing 2265:477–478
Stark C, Breitkreutz BJ, Reguly T, Boucher L, Breitkreutz A, Tyers M (2006) BioGRID: a general repository for interaction datasets. Nucleic Acids Res 34:D535–D539
Navid A, Almaas E (2009) Genome-scale reconstruction of the metabolic network in Yersinia pestis, strain 91001. Mol Biosyst 5:368–375
Newman M (2010) Networks: an introduction. Oxford University Press, New York
Watts DJ, Strogatz SH (1998) Collective dynamics of ‘small-world’ networks. Nature 393:440–442
Newman MEJ (2001) Scientific collaboration networks. II. Shortest paths, weighted networks, and centrality. Phys Rev E 64(1):016132
Sedgewick R (1988) Algorithms, 2nd edn. Addison-Wesley, Reading, Mass
Jeong H, Tombor B, Albert R, Oltvai ZN, Barabasi AL (2000) The large-scale organization of metabolic networks. Nature 407:651–654
Jeong H, Tombor B, Albert R, Oltvai ZN, Barabasi AL (2000) The large-scale organization of metabolic networks. Nature 407:651–654
Gilbert EN (1959) Random graphs. Ann Math Stat 30:1141–1144
Erdos P, Renyi A (1960) On the evolution of random graphs. B Int Statist Inst 38:343–347
Krapivsky PL, Redner S, Leyvraz F (2000) Connectivity of growing random networks. Phys Rev Lett 85:4629–4632
Dorogovtsev SN, Mendes JFF, Samukhin AN (2000) Structure of growing networks with preferential linking. Phys Rev Lett 85:4633–4636
Albert R, Barabasi AL (2000) Topology of evolving networks: local events and universality. Phys Rev Lett 85:5234–5237
Amaral LAN, Scala A, Barthelemy M, Stanley HE (2000) Classes of small-world networks. Proc Natl Acad Sci USA 97:11149–11152
Dorogovtsev SN, Mendes JFF (2000) Evolution of networks with aging of sites. Phys Rev E 62:1842–1845
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer Science+Business Media, LLC
About this protocol
Cite this protocol
Zavareh, Z., Almaas, E. (2012). Complex Network Analysis in Microbial Systems: Theory and Examples. In: Navid, A. (eds) Microbial Systems Biology. Methods in Molecular Biology, vol 881. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-61779-827-6_19
Download citation
DOI: https://doi.org/10.1007/978-1-61779-827-6_19
Published:
Publisher Name: Humana Press, Totowa, NJ
Print ISBN: 978-1-61779-826-9
Online ISBN: 978-1-61779-827-6
eBook Packages: Springer Protocols