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Solving Application Oriented Graph Theoretical Problems with DNA Computing

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Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 201)


Social networks are represented by graphs. Important features of the network, e.g., length of shortest paths, centrality, are given by graph theoretical way. Bipartite graphs are used to represent various problems, for example, in medicine or in economy. The relations between customers and goods can be represented by bipartite graphs. Genes and various diseases can also form a bipartite graph, where a disease is connected to those genes that could cause it. In this paper DNA computing approach is presented for solving some graph theoretical problems. Since DNA computing uses a massively parallel approach, hard graph theoretical problems can be solved (at least in theory). Our main contribution is to present Projection algorithms for bipartite graphs; the molecular tube obtained by them can be used as a base for further processes.


  • DNA computing
  • Graph algorithms
  • Bipartite graphs
  • DNA algorithm
  • Networks
  • Social network
  • Bioinformatics

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  • DOI: 10.1007/978-81-322-1038-2_7
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The authors wish to thank to the reviewers for their valuable remarks. The work is supported by the TÁMOP 4.2.1/B-09/1/KONV-2010-0007 and TÁMOP 4.2.2/C-11/1/KONV-2012-0001 projects. The projects are implemented through the New Hungary Development Plan, co-financed by the European Social Fund and the European Regional Development Fund.

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Correspondence to Veronika Halász .

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© 2013 Springer India

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Halász, V., Hegedüs, L., Hornyák, I., Nagy, B. (2013). Solving Application Oriented Graph Theoretical Problems with DNA Computing. In: Bansal, J., Singh, P., Deep, K., Pant, M., Nagar, A. (eds) Proceedings of Seventh International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA 2012). Advances in Intelligent Systems and Computing, vol 201. Springer, India.

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  • Print ISBN: 978-81-322-1037-5

  • Online ISBN: 978-81-322-1038-2

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