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10.1016/j.compbiomed.2021.104471 http://scihub22266oqcxt.onion/10.1016/j.compbiomed.2021.104471 34004573!8106241!34004573     free     free     free Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Comput+Biol+Med 2021 ; 134 (ä): 104471 Nephropedia Template TP {{tp|p=34004573|t=2021. Image processing unravels the evolutionary pattern of SARS-CoV-2 against SARS and MERS through position-based pattern recognition |pdf=|usr=}}{{34004573}} gab.com Text Image processing unravels the evolutionary pattern of SARS-CoV-2 against SARS and MERS through position-based pattern recognition JO: Comput Biol Med http://www.kidney.de/pget.php?&tw=1&pmid=34004573 #FOAvip SARS-COV-2, Severe Acute Respiratory Syndrome (SARS), and the Middle East respiratory syndrome-related coronavirus (MERS) viruses are from the coronaviridae family; the former became a global pandemic (with low mortality rate) while the latter were confined to a limited region (with high mortality rates). To investigate the possible structural differences at basic levels for the three viruses, genomic and proteomic sequences were downloaded and converted to polynomial datasets. Seven attribute weighting (feature selection) models were employed to find the key differences in their genome's nucleotide sequence. Most attribute weighting models selected the final nucleotide sequences (from 29,000(th) nucleotide positions to the end of the genome) as significantly different among the three virus classes. The genome and proteome sequences of this hot zone area (which corresponds to the 3'UTR region and encodes for nucleoprotein (N)) and Spike (S) protein sequences (as the most important viral protein) were converted into binary images and were analyzed by image processing techniques and Convolutional deep Neural Network (CNN). Although the predictive accuracy of CNN for Spike (S) proteins was low (0.48%), the machine-based learning algorithms were able to classify the three members of coronaviridae viruses with 100% accuracy based on 3'UTR region. For the first time ever, the relationship between the possible structural differences of coronaviruses at the sequential levels and their pathogenesis are being reported, which paves the road to deciphering the high pathogenicity of the SARS-COV-2 virus. Twit Text FOAVip Image processing unravels the evolutionary pattern of SARS-CoV-2 against SARS and MERS through position-based pattern recognition ????Comput Biol Med http://www.kidney.de/pget.php?&tw=1&pmid=34004573 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34004573 #FOAvip English Wikipedia <ref>{{Cite pmid|34004573}}</ref> Image processing unravels the evolutionary pattern of SARS-CoV-2 against SARS and MERS through position-based pattern recognition #MMPMID34004573 Ahsan R; Tahsili MR; Ebrahimi F; Ebrahimie E; Ebrahimi M Comput Biol Med 2021[Jul]; 134 (ä): 104471 PMID34004573show ga SARS-COV-2, Severe Acute Respiratory Syndrome (SARS), and the Middle East respiratory syndrome-related coronavirus (MERS) viruses are from the coronaviridae family; the former became a global pandemic (with low mortality rate) while the latter were confined to a limited region (with high mortality rates). To investigate the possible structural differences at basic levels for the three viruses, genomic and proteomic sequences were downloaded and converted to polynomial datasets. Seven attribute weighting (feature selection) models were employed to find the key differences in their genome's nucleotide sequence. Most attribute weighting models selected the final nucleotide sequences (from 29,000(th) nucleotide positions to the end of the genome) as significantly different among the three virus classes. The genome and proteome sequences of this hot zone area (which corresponds to the 3'UTR region and encodes for nucleoprotein (N)) and Spike (S) protein sequences (as the most important viral protein) were converted into binary images and were analyzed by image processing techniques and Convolutional deep Neural Network (CNN). Although the predictive accuracy of CNN for Spike (S) proteins was low (0.48%), the machine-based learning algorithms were able to classify the three members of coronaviridae viruses with 100% accuracy based on 3'UTR region. For the first time ever, the relationship between the possible structural differences of coronaviruses at the sequential levels and their pathogenesis are being reported, which paves the road to deciphering the high pathogenicity of the SARS-COV-2 virus. |*COVID-19[MESH] |*Middle East Respiratory Syndrome Coronavirus/genetics[MESH] |Humans[MESH] |Pandemics[MESH] |Proteomics[MESH]Image processing unravels the evolutionary pattern of SARS-CoV-2 again(epmc).pdf DeepDyve Pubget Overpricing