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WaRSwap is a randomization algorithm that for the first time provides a practical network motif discovery method for large multi-layer networks, for example those that include transcription factors, microRNAs, and non-regulatory protein coding genes. The algorithm is applicable to systems with tens of thousands of genes, while accounting for critical aspects of biological networks, including self-loops, large hubs, and target rearrangements. We validate WaRSwap on a newly inferred regulatory network from  Arabidopsis thaliana , and compare outcomes on published  Drosophila  and human networks. Specifically, sustained input switches are among the few over-represented circuits across this diverse set of eukaryotes.

Sustained-input switches for transcription factors and microRNAs are central building blocks of eukaryotic gene circuits