18719111

Source:http://linkedlifedata.com/resource/pubmed/id/18719111

Download in:

Switch to

Custom View

Named Graph Language Inference

Statements in which the resource exists as a subject.
Predicate	Object
rdf:type	pubmed:Citation
lifeskim:mentions	umls-concept:C0035647, umls-concept:C0205474, umls-concept:C1882071, umls-concept:C2348693
pubmed:issue	34
pubmed:dateCreated	2008-8-27
pubmed:abstractText	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 less coherent when the fluctuations increase. We also found that the entropy production of the whole network, characterizing the dissipation costs from the combined effects of both landscapes and fluxes, decreases when the fluctuations decrease. Therefore, less dissipation leads to more robust networks. Our approach is quite general and applicable to other networks, dynamical systems, and biological evolution. It can help in designing robust networks.
pubmed:commentsCorrections	http://linkedlifedata.com/resource/pubmed/commentcorrection/18719111-10659856, http://linkedlifedata.com/resource/pubmed/commentcorrection/18719111-11720979, http://linkedlifedata.com/resource/pubmed/commentcorrection/18719111-11792856, http://linkedlifedata.com/resource/pubmed/commentcorrection/18719111-11955179, http://linkedlifedata.com/resource/pubmed/commentcorrection/18719111-12124397, http://linkedlifedata.com/resource/pubmed/commentcorrection/18719111-12237400, http://linkedlifedata.com/resource/pubmed/commentcorrection/18719111-12606710, http://linkedlifedata.com/resource/pubmed/commentcorrection/18719111-12786043, http://linkedlifedata.com/resource/pubmed/commentcorrection/18719111-12787501, http://linkedlifedata.com/resource/pubmed/commentcorrection/18719111-16361441, http://linkedlifedata.com/resource/pubmed/commentcorrection/18719111-17350995, http://linkedlifedata.com/resource/pubmed/commentcorrection/18719111-17381233, http://linkedlifedata.com/resource/pubmed/commentcorrection/18719111-17397255, http://linkedlifedata.com/resource/pubmed/commentcorrection/18719111-1749933, http://linkedlifedata.com/resource/pubmed/commentcorrection/18719111-17916691, http://linkedlifedata.com/resource/pubmed/commentcorrection/18719111-17962411, http://linkedlifedata.com/resource/pubmed/commentcorrection/18719111-18420822, http://linkedlifedata.com/resource/pubmed/commentcorrection/18719111-7886447, http://linkedlifedata.com/resource/pubmed/commentcorrection/18719111-8909137
pubmed:language	eng
pubmed:journal	http://linkedlifedata.com/resource/pubmed/journal/7505876
pubmed:citationSubset	IM
pubmed:status	MEDLINE
pubmed:month	Aug
pubmed:issn	1091-6490
pubmed:author	pubmed-author:LinN CNC, pubmed-author:WangErkangE, pubmed-author:WildE AEA
pubmed:issnType	Electronic
pubmed:day	26
pubmed:volume	105
pubmed:owner	NLM
pubmed:authorsComplete	Y
pubmed:pagination	12271-6
pubmed:dateRevised	2009-11-18
pubmed:meshHeading	pubmed-meshheading:18719111-Biological Clocks, pubmed-meshheading:18719111-Cell Cycle, pubmed-meshheading:18719111-Diffusion, pubmed-meshheading:18719111-Entropy, pubmed-meshheading:18719111-Models, Biological, pubmed-meshheading:18719111-Models, Chemical, pubmed-meshheading:18719111-Models, Theoretical
pubmed:year	2008
pubmed:articleTitle	Potential landscape and flux framework of nonequilibrium networks: robustness, dissipation, and coherence of biochemical oscillations.
pubmed:affiliation	State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin 130022, People's Republic of China. jin.wang.1@stonybrook.edu
pubmed:publicationType	Journal Article, Research Support, Non-U.S. Gov't