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10.1038/ncomms14826 http://scihub22266oqcxt.onion/10.1038/ncomms14826 C5413947!5413947!28429717     free     free     free       Nat+Commun 2017 ; 8 (ä): ä Nephropedia Template TP {{tp|p=28429717|t=2017. Exploratory adaptation in large random networks |pdf=|usr=}}{{28429717}} gab.com Text Exploratory adaptation in large random networks JO: Nat Commun http://www.kidney.de/pget.php?&tw=1&pmid=28429717 #FOAvip The capacity of cells and organisms to respond to challenging conditions in a repeatable manner is limited by a finite repertoire of pre-evolved adaptive responses. Beyond this capacity, cells can use exploratory dynamics to cope with a much broader array of conditions. However, the process of adaptation by exploratory dynamics within the lifetime of a cell is not well understood. Here we demonstrate the feasibility of exploratory adaptation in a high-dimensional network model of gene regulation. Exploration is initiated by failure to comply with a constraint and is implemented by random sampling of network configurations. It ceases if and when the network reaches a stable state satisfying the constraint. We find that successful convergence (adaptation) in high dimensions requires outgoing network hubs and is enhanced by their auto-regulation. The ability of these empirically validated features of gene regulatory networks to support exploratory adaptation without fine-tuning, makes it plausible for biological implementation. Twit Text FOAVip Exploratory adaptation in large random networks ????Nat Commun http://www.kidney.de/pget.php?&tw=1&pmid=28429717 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28429717 #FOAvip English Wikipedia <ref>{{Cite pmid|28429717}}</ref> Exploratory adaptation in large random networks #MMPMID28429717 Schreier HI; Soen Y; Brenner N Nat Commun 2017[]; 8 (ä): ä PMID28429717show ga The capacity of cells and organisms to respond to challenging conditions in a repeatable manner is limited by a finite repertoire of pre-evolved adaptive responses. Beyond this capacity, cells can use exploratory dynamics to cope with a much broader array of conditions. However, the process of adaptation by exploratory dynamics within the lifetime of a cell is not well understood. Here we demonstrate the feasibility of exploratory adaptation in a high-dimensional network model of gene regulation. Exploration is initiated by failure to comply with a constraint and is implemented by random sampling of network configurations. It ceases if and when the network reaches a stable state satisfying the constraint. We find that successful convergence (adaptation) in high dimensions requires outgoing network hubs and is enhanced by their auto-regulation. The ability of these empirically validated features of gene regulatory networks to support exploratory adaptation without fine-tuning, makes it plausible for biological implementation. äExploratory adaptation in large random networks (epmc).pdf DeepDyve Pubget Overpricing