To our knowledge, no maximum common subgraph tool for Cytoscape, able to compare large networks, currently exists. See and for an extensive review of existing global network aligners and commonly used quality measures. The global network alignment problem is equivalent to the MCES problem when the optimized quality measure is the number of fully conserved edges between the aligned graphs. The development of network alignment methods has mainly been motivated by their application to biological knowledge transfer, predicting new interactions and protein structure comparison. Global network alignment methods aim to determine a mapping between the vertices of two or more graphs optimizing some biological or topological quality measure, or a combination of both. The maximum common edge subgraph problem is closely related to the problem of global network alignment.
the number of edges) that is a subgraph of each of the compared graphs. One way of determining this is to compute the maximum common edge subgraph (MCES) between a given set of input graphs, i.e. Comparing different graphs (also called graph alignment) can be used to quantify how similar they are, or to determine whether they all contain some common substructure(s). Graphs are used to model a wide range of biological data including, but not limited to, protein-protein interactions, gene regulatory networks, protein structures and drug-target networks. The analysis and comparison of biological networks (modelled as graphs) is an important problem in computational systems biology.
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