Megraw Molly, Mukherjee Sayan, Ohler Uwe
Genome Biol. 2013 Aug 23;14(8):R85. doi: 10.1186/gb-2013-14-8-r85.
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.
WaRSwap是一种随机化算法,它首次为大型多层网络提供了一种实用的网络基序发现方法,例如那些包含转录因子、微小RNA和非调节性蛋白质编码基因的网络。该算法适用于具有数万个基因的系统,同时考虑了生物网络的关键方面,包括自环、大型枢纽和靶点重排。我们在新推断的拟南芥调控网络上验证了WaRSwap,并比较了已发表的果蝇和人类网络的结果。具体来说,持续输入开关是这组多样化真核生物中少数几个过度代表的回路之一。