Solving application oriented graph theoretical problems with DNA computing

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.