Graph theoretic concepts in the study of biological networks. (English) Zbl 1367.92044

Cushing, Jim M. (ed.) et al., Applied analysis in biological and physical sciences. ICMBAA, Aligarh, India, June 4–6, 2015. New Delhi: Springer (ISBN 978-81-322-3638-2/hbk; 978-81-322-3640-5/ebook). Springer Proceedings in Mathematics & Statistics 186, 187-200 (2016).
Summary: The theory of complex networks has a wide range of applications in a variety of disciplines such as communications and power system engineering, the internet and worldwide web (www), food webs, human social networks, molecular biology, population biology and biological networks. The focus of this paper is on biological applications of the theory of graphs and networks. Graph theory and several graph theoretic properties serve as an ideal mathematical tool in the analysis of complex networks. We present the basic concepts and notations from graph theory which is widely used in the study of biological networks. Various biological networks such as Protein interaction networks, Metabolome based reaction network, Gene regulatory network, Gene coexpression network, Protein structure network, Structural brain network, Phylogenetic networks, Ecological networks and Food web networks are described. We also deal with various centrality measures which provide deep insight in the study of biological networks. Applications of biological network analysis in several areas are also discussed.
For the entire collection see [Zbl 1361.92003].


92C42 Systems biology, networks
05C90 Applications of graph theory
Full Text: DOI


[1] Amitai, G., Shemesh, A., Sitbon, E., Shklar, M., Netanely, D., Venger, I., Pietrokovski, S.: Network analysis of protein structures identifies functional residues. J. Mol. Biol. 344(4), 1135–1146 (2004)
[2] Azuaje, F.J.: Selecting biologically informative genes in coexpression networks with a centrality score. Biol. Direct 9(12), 1–23 (2014)
[3] Barabási, A.L., Albert, R.: Emergence of scaling in random networks. Science 286(5439), 509–512 (1999) · Zbl 1226.05223
[4] Batagelj, V., Mrvar, A.: Pajek - program for large network analysis. Connections 21, 47–57 (1998)
[5] Baths, V., Roy, U., Singh, T.: Disruption of cell wall fatty acid biosynthesis in Mycobacterium tuberculosis using a graph theoretic approach. Theor. Biol. Med. Model. 8(5), 1–13 (2011)
[6] Bonacich, P.: Factoring and weighting approaches to status scores and clique identification. J. Math. Sociol. 2, 113–120 (1972)
[7] Bullmore, E.D., Sporns, O.: Complex brain networks graph theoretical analysis of structural and functional systems. Nature Rev. Neurosci. 10, 186–198 (2009)
[8] Chartrand, G., Lesniak, L.: Graphs & Digraphs, 4th edn. Chapman and Hall, CRC, Boca Raton (2005)
[9] Christensen, C., Gupta, A., Maranas, C.D., Albert, R.: Large scale inference and graph theoretical analysis of gene-regulatory networks in B. Subtilis. Physica A 373, 796–810 (2007)
[10] Dunne, J.A., Williams, R.J., Martinez, N.D.: Food-web structure and network theory: the role of connectance and size. PNAS 99(20), 12917–12922 (2002)
[11] Erdös, P., Rényi, A.: On the strength of connectedness of a random graph. Acta Mathematica Academiae Scientiarum Hungarica 12, 261–267 (1964) · Zbl 0103.16302
[12] Estrada, E.: Virtual identification of essential protein within the protein interaction network of yeast. Proteomics 6(1), 35–40 (2006)
[13] Estrada, E., Rodríguez-Velázquez, J.A..: Subgraph centrality in complex networks. Phys. Rev. 71 (2005)
[14] Fuller, T.F., Ghazalpour, A., Aten, J.E., Drake, T.A., Lusis, A.J., Horrath, S.: Weighted gene coexpression network analysis strategies applied to mouse weight. Mamm Genome 18(6–7), 463–472 (2007)
[15] Goh, K.I., Cusick, M.E., Valle, D., Childs, B., Vidal, M., Barabási, A.: The human disease network. Proc. National Acad. Sci. 104(21), 8685–8690 (2007)
[16] Hu, Z., Mellor, J., Wu, J., Yamada, T., Holloway, D., DeLisi, C.: VisANT: data-integrating visual framework for biological networks and modules. Nucleic Acids Res. 33, 352–357 (2005) · Zbl 05437628
[17] Huson, D.H., Rupp, R., Scornavacca, C.: Phylogenetic Networks. Cambridge University Press, Cambridge (2010)
[18] Jensen, L.J., Kuhn, M., Stark, M., Chaffron, S., Creevey, C., Muller, J., Doerks, T., Julien, P., Roth, A., Simonovic, M., Bork, P., von Mering, C.: STRING 8-a global view on proteins and their functional interactions in 630 organisms. Nucleic Acids Res. 37, 412–416 (2009) · Zbl 05746565
[19] Jiang, W., Li, X., Rao, S., Wang, L., Du, L., Li, C., Wu, C., Wang, H., Wang, Y., Yang, B.: Constructing disease-specific gene networks using pair-wise relevance metric: application to colon cancer identifies interleukin 8, desmin and enolase 1 as the central elements. BMC Syst. Biol. 2(1), 72 (2008)
[20] Joshi-Tope, G., Gillespie, M., Vastrik, I., D’Eustachio, P., Schmidt, E., de Bono, B., Jassal, B., Gopinath, G.R., Wu, G.R., Matthews, L., Lewis, S., Birney, E., Stein, L.: Reactome: a knowledgebase of biological pathways. Nucleic Acids Res. 33, 428–432 (2005) · Zbl 05437316
[21] Kanehisa, M., Goto, S., Furumichi, M., Tanabe, M., Hirakawa, M.: KEGG for representation and analysis of molecular networks involving diseases and drugs. Nucleic Acids Res. 38, 355–360 (2010) · Zbl 05891956
[22] Kerrien, S., Alam-Faruque, Y., Aranda, B., Bancarz, I., Bridge, A., Derow, C., Dimmer, E., Feuermann, M., Friedrichsen, A., Huntley, R., Kohler, C., Khadake, J., Leroy, C., Liban, A., Lieftink, C., Montecchi-Palazzi, L., Orchard, S., Risse, J., Robbe, K., Roechert, B., Thorneycroft, D., Zhang, Y., Apweiler, R., Hermjakob, H.: IntAct-open source resource for molecular interaction data. Nucleic Acids Res. 35, 561–565 (2007) · Zbl 05438239
[23] Keshava Prasad, T.S., Goel, R., Kandasamy, K., Keerthikumar, S., Kumar, S., Mathivanan, S., Telikicherla, D., Raju, R., Shafreen, B., Venugopal, A., Balakrishnan, L., Marimuthu, A., Banerjee, S., Somanathan, D.S., Sebastian, A., Rani, S., Ray, S., Harrys Kishore, C.J., Kanth, S., Ahmed, M., Kashyap, M.K., Mohmood, R., Ramachandra, Y.L., Krishna, V., Abdul Rahiman, B., Mohan, S., Ranganathan, P., Ramabadran, S., Chaerkady, R., Pandey, A.: Human protein reference database. Nucleic Acids Res. 37, 767–772 (2009) · Zbl 05746624
[24] Memisevic, V., Milenkovic, T., Przulj, N.: An integrative approach to modeling biological networks. J. Integr. Bioinform. 7(3), 1–22 (2010)
[25] Milo, R., Shen-Orr, S., Itzkovitz, S., Kashtan, N., Chklovskii, D., Alon, U.: Network motifs: simple building blocks of complex networks. Science 298(5594), 824–827 (2002)
[26] Mukhopadhyay, A., Maulik, U.: Network-based study reveals potential infection pathways of Hepatitis-C leading to various diseases. PLOS One 9(4), 1–12 (2014)
[27] Paz, A., Brownstein, Z., Ber, Y., Bialik, S., David, E., Sagir, D., Ulitsky, I., Elkon, R., Kimchi, A., Avraham, K.B., Shiloh, Y., Shamir, R.: SPIKE: a database of highly curated human signaling pathways. Nucleic Acids Res. 39, 793–799 (2011) · Zbl 05892299
[28] Perkins, A.D., Langston, M.A.: Threshold selection in gene coexpression networks using spectral graph theory techniques. BMC Bioinform. 10(54), 1–11 (2008)
[29] Raza, K., Jaiswal, R.: Reconstruction and analysis of cancer-specific gene regulatory networks from gene expression profiles. Int. J. Bioinform. Biosci. 3(2), 25–34 (2013)
[30] Scardoni, G., Laudana, C.: Centralities based analysis of complex networks. In: Zhang, Y. (ed.) New Frontiers in Graph Theory, InTech (2012)
[31] Shannon, P., Markiel, A., Ozier, O., Baliga, N.S., Wang, J.T., Ramage, D., Amin, N., Schwikowski, B., Idekar, T.: Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 13(11), 2498–2504 (2003)
[32] Sole, R.V., Montoya, J.M.: Complexity and fragility in ecological networks. Proc. R. Soc. Lond. B 268, 2039–2045 (2001)
[33] Stark, C., Breitkreutz, B.J., Reguly, T., Boucher, L., Breitkreutz, A., Tyers, M.: BioGRID: a general repository for interaction datasets. Nucleic Acids Res. 34, 535–539 (2006) · Zbl 05437835
[34] Watts, D.J., Strogatz, S.H.: Collective dynamics of ’small-world’ networks. Nature 393, 440–442 (1998) · Zbl 1368.05139
[35] Xenarios, I., Rice, D.W., Salwinski, L., Baron, M.K., Marcotte, E.M., Eisenberg, D.: DIP: the database of interacting proteins. Nucleic Acids Res. 28(1), 289–291 (2000) · Zbl 05437357
[36] Yue, H., Chunmei, L.: Study of Gene regulatory network based on graph. In: 4th International Conference on Biomedical Engineering and Informatics, pp. 2236–2240. IEEE (2011)
[37] Zanzoni, A., Montecchi-Palazzi, L., Quondam, M., Ausiello, G., Helmer-Citterich, M., Cesareni, G.: MINT: a Molecular INTeraction database. FEBS Lett. 513(1), 135–140 (2002)
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