DynaMAGNA++ appeared in the following publication: Vipin Vijayan, Dominic Critchlow, and Tijana Milenkovic (2017), Alignment of dynamic networks, Bioinformatics, 33(14): i180-i189, 2017.

DynaMAGNA++ is the first ever method for pairwise global alignment of dynamic networks. Dynamic networks are networks that evolve over time. Existing methods can only align static networks. However, most complex real-world systems evolve over time and should thus be modeled as dynamic networks. So, we introduce DynaMAGNA++ to allow for aligning such networks. An example of an application domain where DynaMAGNA++ is useful is computational biology, where DynaMAGNA++ can be used for alignment of molecular networks that evolve over time. Other domains include social networks, computer vision, ontology matching, etc.

DynaMAGNA++ is an extension of a state-of-the-art static network alignment method called MAGNA++. Even though both MAGNA++ and DynaMAGNA++ optimize edge as well as node conservation across the aligned networks, MAGNA++ conserves static edges and similarity between static node neighborhoods, while DynaMAGNA++ conserves dynamic edges (events) and similarity between evolving node neighborhoods. MAGNA++ appears in the following publication: Vipin Vijayan, Vikram Saraph, and Tijana Milenkovic, MAGNA++: Maximizing Accuracy in Global Network Alignment via both node and edge conservation, Bioinformatics, 31(14): 2409-2411, 2015.

The executables and source code of DynaMAGNA++ are available for download, along with detailed usage instructions. You can also download example networks.

Vipin Vijayan may be contacted via email at vvijayan [at] nd [dot] edu and Tijana Milenkovic can be contacted via email at tmilenko [at] nd [dot] edu.