Triangular Alignment (TAME): A Tensor-Based Approach for Higher-Order Network Alignment

@article{Mohammadi2017TriangularA,
  title={Triangular Alignment (TAME): A Tensor-Based Approach for Higher-Order Network Alignment},
  author={Shahin Mohammadi and David F. Gleich and Tamara G. Kolda and Ananth Y. Grama},
  journal={IEEE/ACM Transactions on Computational Biology and Bioinformatics},
  year={2017},
  volume={14},
  pages={1446-1458}
}
Network alignment has extensive applications in comparative interactomics. Traditional approaches aim to simultaneously maximize the number of conserved edges and the underlying similarity of aligned entities. We propose a novel formulation of the network alignment problem that extends topological similarity to higher-order structures and provides a new objective function that maximizes the number of aligned substructures. This objective function corresponds to an integer programming problem… CONTINUE READING