Comparative analysis of various modularization algorithms and species specific study of VEGF signaling pathways

Namrata Tomar, Losiana Nayak, Rajat K. De

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DOI: 10.4236/jbise.2010.310124                

Abstract

In biology, signal transduction refers to a process by which a cell converts one kind of signal or stimulus into another. It involves ordered sequences of biochemical reactions inside the cell. These cascades of reactions are carried out by enzymes and activated by second messengers. Signal transduction pathways are complex in nature. Each pathway is responsible for tuning one or more biological functions in the intracellular environment as well as more than one pathway interact among themselves to carry forward a single biological function. Such kind of behavior of these pathways makes understanding difficult. Hence, for the sake of simplicity, they need to be partitioned into smaller modules and then analyzed. We took VEGF signaling pathway, which is responsible for angiogenesis for this kind of modularized study. Modules were obtained by applying the algorithm of Nayak and De (Nayak and De, 2007) for different complexity values. These sets of modules were compared among themselves to get the best set of modules for an optimal complexity value. The best set of modules compared with four different partitioning algorithms namely, Farhat’s (Farhat, 1998), Greedy (Chartrand and Oellermann, 1993), Kernighan-Lin’s (Kernighan and Lin, 1970) and Newman’s community finding algorithm (Newman, 2006). These comparisons enabled us to decide which of the aforementioned algorithms was the best one to create partitions from human VEGF signaling pathway. The optimal complexity value, on which the best set of modules was obtained, was used to get modules from different species for comparative study. Comparison among these modules would shed light on the trend of development of VEGF signaling pathway over these species.

Keywords

Signal Transduction Pathway, VEGF Pathway, Complexity Value, KEGG Database, Modularization, Newman’s Community Finding Algorithm, Kernighan-Lin’s Algorithm, Farhat’s Algorithm, and Greedy Algorithm.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	Twyman, R.M. (2000) Advanced molecular biology. Garland/BIOS Scientific Publishers, UK.
[2]	David, L.N. and Cox, M.M. (2008) Lehninger principles of biochemistry. 5th Edition, W. H. Freeman & Company, New York.
[3]	Nayak, L. and De, R. (2007) An algorithm for modularization of MAPK and calcium signaling pathways: Comparative analysis among different species. Journal of Biomedical Informatics, 40(6), 726-749.
[4]	Robinson, C.J. and Stringer, S.E. (2001) The splice variants of vascular endothelial growth factor (VEGF) and their receptors. Journal of Cell Science, 114(5), 853-865.
[5]	Kowanetz, M. and Ferrara, N. (2006) Vascular endothelial growth factor signaling pathways: Therapeutic perspective. Clinical Cancer Research, 12(17), 5018-5022.
[6]	Breslin, J.W., Pappas, P.J., Cerveira, J.J., Hobson, R.W. and Durn, W.N. (2002) VEGF increases endothelial permeability by separate signaling pathways involving ERK-1/2 and nitric oxide. American Journal of Physiologic Heart Circ Physiology, 284(1), H92-H100.
[7]	Kernighan, B.W. and Lin, S. (1970) An efficient heuristic procedure for partitioning graphs. The Bell System Technical Journal, 49, 291-307.
[8]	Chartrand, G. and Oellermann, O.R. (1993) Applied and algorithmic graph theory. International Series in Pure and Applied Mathematics. McGraw Hill, New York.
[9]	Farhat, C.G. (1988) A simple and efficient automatic fem domain decomposer. Computers & Structures, 28(5), 579-602.
[10]	Newman, M.E.J. (2006) Modularity and community structure in networks. PNAS, 103(23), 8577-8582.
[11]	McLaughlin, A.P. and Vries, G.W.D. (2001) Role of PLCg and Ca2+ in VEGF and FGF-induced choroidal endothelial cell proliferation. American Journal of Physiologic Cell Physiology, 281(5), C1448-C1456.
[12]	Hunag, C., Jacobson, K. and Schallerl, M.D. (2004) MAP Kinases and cell migration. Journal of Cell Science, 117, 4619-4628.
[13]	Blum, S., Issbrucker, K., Willuweit, A., Hehlgans, S., Lucerna, M., Mechtcheriakova, D., Walsh, K.V.D., Ahe, D., Hofer, E. and Clauss, M. (2001) An inhibitory role of the phosphatidylinositol 3-kinase-signaling pathway in vascular endothelial growth factor-induced tissue factor expression. The Journal of Biochemistry, 276(36), 33428-33434.
[14]	Horsley, V. and Pavlath, G.K. (2002) NFAT: Ubiquitous regulator of cell differentiation and adaptation. The Journal of Cell Biology, 156(5), 771- 774.
[15]	Armesilla, A.L., Lorenzo, E., Arco, P.G.D., Martinez S., Alfranca, A. and Redondo, J.M. (1999) Vascular endothelial growth factor activates nuclear factor of activated T cells in human endothelial cells: A role for tissue factor gene expression. Molecular and Cellular Biology, 19(3), 2032-2043.