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Assortativity signatures of transcription factor networks contribute to robustness
Date:8/29/2014

s evaluated the assortativity signatures in published TFNs of 41 distinct human cell and tissue types and found that an above average number of connected TFs had similar numbers of outgoing connections (high out-out assortativity). Furthermore, this property, more so than the other three types of assortativity, seemed to be a predictor of robustness.

"Robustness is a measure of how resilient an overall pattern of TF gene expression is over time when confronted with mutations in the regulatory instructions of these TFs. If mutations tend to change the pattern, then robustness is low. If mutations tend to have no effect on the pattern, then robustness is high," said Pechenick.

This Dartmouth study was the first to look at the assortativity signatures of TFNs and their impact on robustness. "Results suggest that measuring the assortativity signature of a TFN can tell you something about its robustness," said Pechenick. "For researchers that wish to understand and simulate biological networks, these results indicate the importance of considering assortativity."


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Contact: Donna Dubuc
Donna.M.Dubuc@Dartmouth.edu
603-653-3615
The Geisel School of Medicine at Dartmouth
Source:Eurekalert

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