Network alignment can be used to transfer functional knowledge between conserved
regions of different networks. Existing methods use a node cost function (NCF) to compare …

Motivation: Network alignment aims to find conserved regions between different networks.
Existing methods aim to maximize total similarity over all aligned nodes (ie node …

Motivation: Biological network alignment aims to identify similar regions between networks
of different species. Existing methods compute node similarities to rapidly identify from …

Network alignment (NA) aims to find a node mapping that identifies topologically or
functionally similar network regions between molecular networks of different species …

Network alignment (NA) aims to find similar (conserved) regions between networks. Until
recently, existing methods were limited to aligning static networks. However, real-world …

Network alignment (NA) compares networks with the goal of finding a node mapping that
uncovers highly similar (conserved) network regions. Existing NA methods are …

Network alignment aims to find regions of topological or functional similarities between
networks. In computational biology, it can be used to transfer biological knowledge from a …

Every alignment algorithm consists of two orthogonal components: an objective function M
measuring the quality of an alignment, and a search algorithm that explores the space of …

Networks are successfully used as a modelling framework in many application domains. For
instance, Protein-Protein Interaction Networks (PPINs) model the set of interactions among …

Background Analogous to genomic sequence alignment, biological network alignment
identifies conserved regions between networks of different species. Then, function can be …