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10.1016/j.jtbi.2015.07.011 http://scihub22266oqcxt.onion/10.1016/j.jtbi.2015.07.011 C4572021!4572021 !26215686     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=26215686 &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 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\26215686 .jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       J+Theor+Biol 2015 ; 383 (ä): 28-43 Nephropedia Template TP {{tp|p=26215686 |t=2015. Toward a unifying framework for evolutionary processes |pdf=|usr=}}{{26215686 }} gab.com Text Toward a unifying framework for evolutionary processes JO: J Theor Biol http://www.kidney.de/pget.php?&tw=1&pmid=26215686 #FOAvip The theory of population genetics and evolutionary computation have been evolving separately for nearly 30 years. Many results have been independently obtained in both fields and many others are unique to its respective field. We aim to bridge this gap by developing a unifying framework for evolutionary processes that allows both evolutionary algorithms and population genetics models to be cast in the same formal framework. The framework we present here decomposes the evolutionary process into its several components in order to facilitate the identification of similarities between different models. In particular, we propose a classification of evolutionary operators based on the defining properties of the different components. We cast several commonly used operators from both fields into this common framework. Using this, we map different evolutionary and genetic algorithms to different evolutionary regimes and identify candidates with the most potential for the translation of results between the fields. This provides a unified description of evolutionary processes and represents a stepping stone towards new tools and results to both fields. Twit Text FOAVip Toward a unifying framework for evolutionary processes ????J Theor Biol http://www.kidney.de/pget.php?&tw=1&pmid=26215686 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=26215686 #FOAvip English Wikipedia <ref>{{Cite pmid|26215686 }}</ref> Toward a unifying framework for evolutionary processes #MMPMID26215686 Paixão T ; Badkobeh G ; Barton N ; Çörü? D ; Dang DC ; Friedrich T ; Lehre PK ; Sudholt D ; Sutton AM ; Trubenová B J Theor Biol 2015[Oct]; 383 (ä): 28-43 PMID26215686 show ga The theory of population genetics and evolutionary computation have been evolving separately for nearly 30 years. Many results have been independently obtained in both fields and many others are unique to its respective field. We aim to bridge this gap by developing a unifying framework for evolutionary processes that allows both evolutionary algorithms and population genetics models to be cast in the same formal framework. The framework we present here decomposes the evolutionary process into its several components in order to facilitate the identification of similarities between different models. In particular, we propose a classification of evolutionary operators based on the defining properties of the different components. We cast several commonly used operators from both fields into this common framework. Using this, we map different evolutionary and genetic algorithms to different evolutionary regimes and identify candidates with the most potential for the translation of results between the fields. This provides a unified description of evolutionary processes and represents a stepping stone towards new tools and results to both fields. |*Biological Evolution [MESH] |*Models, Genetic [MESH] |Algorithms [MESH] |Animals [MESH] |Genetics, Population [MESH]Toward a unifying framework for evolutionary processes (epmc).pdf DeepDyve Pubget Overpricing