Potential landscape and flux framework of nonequilibrium networks: robustness, dissipation, and coherence of biochemical oscillations.

Proceedings of the National Academy of Sciences of the United States of America
Jin WangErkang Wang

Abstract

We established a theoretical framework for studying nonequilibrium networks with two distinct natures essential for characterizing the global probabilistic dynamics: the underlying potential landscape and the corresponding curl flux. We applied the idea to a biochemical oscillation network and found that the underlying potential landscape for the oscillation limit cycle has a distinct closed ring valley (Mexican hat-like) shape when the fluctuations are small. This global landscape structure leads to attractions of the system to the ring valley. On the ring, we found that the nonequilibrium flux is the driving force for oscillations. Therefore, both structured landscape and flux are needed to guarantee a robust oscillating network. The barrier height separating the oscillation ring and other areas derived from the landscape topography is shown to be correlated with the escaping time from the limit cycle attractor and provides a quantitative measure of the robustness for the network. The landscape becomes shallower and the closed ring valley shape structure becomes weaker (lower barrier height) with larger fluctuations. We observe that the period and the amplitude of the oscillations are more dispersed and oscillations become le...Continue Reading

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Citations

Apr 16, 2010·Proceedings of the National Academy of Sciences of the United States of America·Jin WangErkang Wang
Oct 13, 2010·Proceedings of the National Academy of Sciences of the United States of America·Youfang CaoJie Liang
May 19, 2010·Proceedings of the National Academy of Sciences of the United States of America·F RemacleR D Levine
May 4, 2011·Proceedings of the National Academy of Sciences of the United States of America·Jin WangErkang Wang
Aug 31, 2011·Proceedings of the National Academy of Sciences of the United States of America·Shenshen Wang, Peter G Wolynes
Aug 28, 2013·Proceedings of the National Academy of Sciences of the United States of America·Kun ZhangJin Wang
Sep 26, 2013·Proceedings of the National Academy of Sciences of the United States of America·Jason R GreenIgal Szleifer
Aug 31, 2012·Journal of the Royal Society, Interface·Joseph Xu ZhouSui Huang
Jul 6, 2011·Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences·Sui Huang
May 31, 2011·BMC Systems Biology·Sudin BhattacharyaMelvin E Andersen
Oct 25, 2011·PLoS Computational Biology·Mark HallenLingchong You
Jan 5, 2012·PLoS Computational Biology·Rui ChangWei Wang
Dec 5, 2012·PLoS Computational Biology·Yihan LinNorbert F Scherer
Dec 19, 2013·PLoS Computational Biology·Masaki SasaiTomoki P Terada
Mar 29, 2014·PLoS Computational Biology·Samanthe M LyonsAshok Prasad
Feb 6, 2014·PloS One·Li XuJin Wang
Oct 23, 2013·Proceedings of the National Academy of Sciences of the United States of America·Han YanJin Wang
Aug 18, 2012·The Journal of Chemical Physics·Feng ZhangJin Wang
Jan 29, 2014·Proceedings of the National Academy of Sciences of the United States of America·Davit A Potoyan, Peter G Wolynes
Apr 9, 2014·BMC Systems Biology·Berta VerdJohannes Jaeger
Jun 21, 2014·Proceedings of the National Academy of Sciences of the United States of America·Bin Zhang, Peter G Wolynes
Sep 19, 2014·Journal of the Royal Society, Interface·Chunhe Li, Jin Wang
Oct 17, 2014·Journal of the Royal Society, Interface·Guanyu Wang
Jan 1, 2010·Journal of Computer Science and Technology·Jie Liang, Hong Qian
Sep 18, 2014·Proceedings of the National Academy of Sciences of the United States of America·Chunhe Li, Jin Wang
Jun 7, 2011·Seminars in Cancer Biology·Sui Huang
Dec 15, 2010·Trends in Genetics : TIG·Joseph X Zhou, Sui Huang
Dec 8, 2015·The Journal of Physical Chemistry. B·Yutaka NagahataTamiki Komatsuzaki
Dec 10, 2015·The Journal of Chemical Physics·Michael ManhartAlexandre V Morozov
Apr 29, 2011·Molecular Systems Biology·Guang YaoLingchong You

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