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10.1016/j.gene.2021.145470 http://scihub22266oqcxt.onion/10.1016/j.gene.2021.145470 33549714!7860943!33549714     free     free     free Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Gene 2021 ; 778 (ä): 145470 Nephropedia Template TP {{tp|p=33549714|t=2021. Mutational analysis and assessment of its impact on proteins of SARS-CoV-2 genomes from India |pdf=|usr=}}{{33549714}} gab.com Text Mutational analysis and assessment of its impact on proteins of SARS-CoV-2 genomes from India JO: Gene http://www.kidney.de/pget.php?&tw=1&pmid=33549714 #FOAvip Mutational status of SARS-CoV-2 genomes from India along with their impact on proteins was ascertained through multiple tools including MEGA, Genome Detective, SIFT, PROVEAN and ws-SNPs&GO. Excluding gaps and ambiguous sequences, 493 variable sites (152 parsimony informative and 341 singleton) were observed. NSP3 had the highest incidence of 101 sites followed by S protein (74), NSP12b (43) and ORF3a (31). Average mutations per sample for males and females was 2.56 and 2.88 respectively. Non-uniform geographical distribution of mutations suggests that sequences in some regions are mutating faster than others. There were 281 mutations (198 Neutral and 83 Disease) affecting amino acid sequence. NSP13 has a maximum of 14 Disease variants followed by S protein and ORF3a with 13 each. Disease mutations in genomes from asymptomatic people was mere 11% but those from deceased patients was at 38% indicating contribution of these mutations to the pathophysiology of the SARS-CoV-2. Twit Text FOAVip Mutational analysis and assessment of its impact on proteins of SARS-CoV-2 genomes from India ????Gene http://www.kidney.de/pget.php?&tw=1&pmid=33549714 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33549714 #FOAvip English Wikipedia <ref>{{Cite pmid|33549714}}</ref> Mutational analysis and assessment of its impact on proteins of SARS-CoV-2 genomes from India #MMPMID33549714 Laskar R; Ali S Gene 2021[Apr]; 778 (ä): 145470 PMID33549714show ga Mutational status of SARS-CoV-2 genomes from India along with their impact on proteins was ascertained through multiple tools including MEGA, Genome Detective, SIFT, PROVEAN and ws-SNPs&GO. Excluding gaps and ambiguous sequences, 493 variable sites (152 parsimony informative and 341 singleton) were observed. NSP3 had the highest incidence of 101 sites followed by S protein (74), NSP12b (43) and ORF3a (31). Average mutations per sample for males and females was 2.56 and 2.88 respectively. Non-uniform geographical distribution of mutations suggests that sequences in some regions are mutating faster than others. There were 281 mutations (198 Neutral and 83 Disease) affecting amino acid sequence. NSP13 has a maximum of 14 Disease variants followed by S protein and ORF3a with 13 each. Disease mutations in genomes from asymptomatic people was mere 11% but those from deceased patients was at 38% indicating contribution of these mutations to the pathophysiology of the SARS-CoV-2. |*Genome, Viral[MESH] |*Mutation[MESH] |*Sequence Analysis, Protein[MESH] |COVID-19/epidemiology/*genetics[MESH] |Humans[MESH] |India/epidemiology[MESH] |SARS-CoV-2/*genetics/pathogenicity[MESH]Mutational analysis and assessment of its impact on proteins of SARS-C(epmc).pdf DeepDyve Pubget Overpricing