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10.1038/s41598-022-14404-6 http://scihub22266oqcxt.onion/10.1038/s41598-022-14404-6 35717436!9206224!35717436     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Sci+Rep 2022 ; 12 (1): 10297 Nephropedia Template TP {{tp|p=35717436|t=2022. Relating SARS-CoV-2 variants using cellular automata imaging |pdf=|usr=}}{{35717436}} gab.com Text Relating SARS-CoV-2 variants using cellular automata imaging JO: Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=35717436 #FOAvip We classify the main variants of the SARS-CoV-2 virus representing a given biological sequence coded as a symbolic digital sequence and by its evolution by a cellular automata with a properly chosen rule. The spike protein, common to all variants of the SARS-CoV-2 virus, is then by the picture of the cellular automaton evolution yielding a visible representation of important features of the protein. We use information theory Hamming distance between different stages of the evolution of the cellular automaton for seven variants relative to the original Wuhan/China virus. We show that our approach allows to classify and group variants with common ancestors and same mutations. Although being a simpler method, it can be used as an alternative for building phylogenetic trees. Twit Text FOAVip Relating SARS-CoV-2 variants using cellular automata imaging ????Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=35717436 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=35717436 #FOAvip English Wikipedia <ref>{{Cite pmid|35717436}}</ref> Relating SARS-CoV-2 variants using cellular automata imaging #MMPMID35717436 Souza LF; Rocha Filho TM; Moret MA Sci Rep 2022[Jun]; 12 (1): 10297 PMID35717436show ga We classify the main variants of the SARS-CoV-2 virus representing a given biological sequence coded as a symbolic digital sequence and by its evolution by a cellular automata with a properly chosen rule. The spike protein, common to all variants of the SARS-CoV-2 virus, is then by the picture of the cellular automaton evolution yielding a visible representation of important features of the protein. We use information theory Hamming distance between different stages of the evolution of the cellular automaton for seven variants relative to the original Wuhan/China virus. We show that our approach allows to classify and group variants with common ancestors and same mutations. Although being a simpler method, it can be used as an alternative for building phylogenetic trees. |*COVID-19/genetics[MESH] |*SARS-CoV-2/genetics[MESH] |Cellular Automata[MESH] |Genome, Viral[MESH] |Humans[MESH] |Mutation[MESH]Relating SARS-CoV-2 variants using cellular automata imaging (epmc).pdf DeepDyve Pubget Overpricing