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10.1063/1.4807733 http://scihub22266oqcxt.onion/10.1063/1.4807733 C3689811!3689811 !23822502     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=23822502 &cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215       Chaos 2013 ; 23 (2 ): 025104 Nephropedia Template TP {{tp|p=23822502 |t=2013. Causal structure of oscillations in gene regulatory networks: Boolean analysis of ordinary differential equation attractors |pdf=|usr=}}{{23822502 }} gab.com Text Causal structure of oscillations in gene regulatory networks: Boolean analysis of ordinary differential equation attractors JO: Chaos http://www.kidney.de/pget.php?&tw=1&pmid=23822502 #FOAvip A common approach to the modeling of gene regulatory networks is to represent activating or repressing interactions using ordinary differential equations for target gene concentrations that include Hill function dependences on regulator gene concentrations. An alternative formulation represents the same interactions using Boolean logic with time delays associated with each network link. We consider the attractors that emerge from the two types of models in the case of a simple but nontrivial network: a figure-8 network with one positive and one negative feedback loop. We show that the different modeling approaches give rise to the same qualitative set of attractors with the exception of a possible fixed point in the ordinary differential equation model in which concentrations sit at intermediate values. The properties of the attractors are most easily understood from the Boolean perspective, suggesting that time-delay Boolean modeling is a useful tool for understanding the logic of regulatory networks. Twit Text FOAVip Causal structure of oscillations in gene regulatory networks: Boolean analysis of ordinary differential equation attractors ????Chaos http://www.kidney.de/pget.php?&tw=1&pmid=23822502 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=23822502 #FOAvip English Wikipedia <ref>{{Cite pmid|23822502 }}</ref> Causal structure of oscillations in gene regulatory networks: Boolean analysis of ordinary differential equation attractors #MMPMID23822502 Sun M ; Cheng X ; Socolar JE Chaos 2013[Jun]; 23 (2 ): 025104 PMID23822502 show ga A common approach to the modeling of gene regulatory networks is to represent activating or repressing interactions using ordinary differential equations for target gene concentrations that include Hill function dependences on regulator gene concentrations. An alternative formulation represents the same interactions using Boolean logic with time delays associated with each network link. We consider the attractors that emerge from the two types of models in the case of a simple but nontrivial network: a figure-8 network with one positive and one negative feedback loop. We show that the different modeling approaches give rise to the same qualitative set of attractors with the exception of a possible fixed point in the ordinary differential equation model in which concentrations sit at intermediate values. The properties of the attractors are most easily understood from the Boolean perspective, suggesting that time-delay Boolean modeling is a useful tool for understanding the logic of regulatory networks. |*Algorithms [MESH] |*Gene Regulatory Networks [MESH]Causal structure of oscillations in gene regulatory networks: Boolean (epmc).pdf DeepDyve Pubget Overpricing