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Open Access Method

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

Molly Megraw178*, Sayan Mukherjee234 and Uwe Ohler1356

Author affiliations

1 Institute for Genome Sciences and Policy, Duke University, 101 Science Drive, Durham, NC 27708, USA

2 Department of Statistical Science, Duke University, Box 90251, Durham, NC 27708, USA

3 Computer Science, Duke University, 308 Research Drive, Durham, NC 27708, USA

4 Department of Mathematics, Duke University, 120 Science Drive, Durham, NC 27708, USA

5 Department of Biostatistics and Bioinformatics, Duke University, 2424 Erwin Road, Durham, NC 27710, USA

6 Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine, Robert-Rössle-Strasse 10, 13125 Berlin, Germany

7 Center for Genome Research and Biocomputing, Oregon State University, 2750 SW Campus Way, Corvallis, OR 97331, USA

8 Department of Botany and Plant Pathology, Oregon State University, 2701 SW Campus Way, Corvallis, OR, USA

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Citation and License

Genome Biology 2013, 14:R85  doi:10.1186/gb-2013-14-8-r85

Published: 23 August 2013

Abstract

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.

Keywords:
gene regulation; microRNA; network motif; transcription factor