Aligning dynamic networks with DynaWAVE
Network alignment (NA) aims to find similar (conserved) regions between networks, such as cellular networks of different species. Until recently, existing methods were limited to aligning static networks. However, real-world systems, including cellular functioning, are dynamic. Hence, in our previous work, we introduced the first ever dynamic NA method, DynaMAGNA++, which improved upon the traditional static NA. However, DynaMAGNA++ does not necessarily scale well to larger networks in terms of alignment quality or runtime.Results:
To address this, we introduce a new dynamic NA approach, DynaWAVE. We show that DynaWAVE complements DynaMAGNA++: while DynaMAGNA++ is more accurate yet slower than DynaWAVE for smaller networks, DynaWAVE is both more accurate and faster than DynaMAGNA++ for larger networks. We provide a friendly user interface and source code for DynaWAVE.Availability and implementation:
Supplementary data are available at Bioinformatics online.