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10.2174/1573409917666210202092646 http://scihub22266oqcxt.onion/10.2174/1573409917666210202092646 33530913!ä!33530913 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 247.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 247.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 247.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 247.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 247.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 247.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 280.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Curr+Comput+Aided+Drug+Des 2021 ; 17 (7): 936-945 Nephropedia Template TP {{tp|p=33530913|t=2021. Cluster Analysis of Coronavirus Sequences using Computational Sequence Descriptors: With Applications to SARS, MERS and SARS-CoV-2 (CoVID-19) |pdf=|usr=}}{{33530913}} gab.com Text Cluster Analysis of Coronavirus Sequences using Computational Sequence Descriptors: With Applications to SARS, MERS and SARS-CoV-2 (CoVID-19) JO: Curr Comput Aided Drug Des http://www.kidney.de/pget.php?&tw=1&pmid=33530913 #FOAvip INTRODUCTION: Coronaviruses comprise a group of enveloped, positive-sense single-stranded RNA viruses that infect humans as well as a wide range of animals. The study was performed on a set of 573 sequences belonging to SARS, MERS and SARS-CoV-2 (CoVID-19) viruses. The sequences were represented with alignment-free sequence descriptors and analyzed with different chemometric methods: Euclidean/Mahalanobis distances, principal component analysis and self-organizing maps (Kohonen networks). We report the cluster structures of the data. The sequences are well-clustered regarding the type of virus; however, some of them show the tendency to belong to more than one virus type. BACKGROUND: This is a study of 573 genome sequences belonging to SARS, MERS and SARS-- CoV-2 (CoVID-19) coronaviruses. OBJECTIVES: The aim was to compare the virus sequences, which originate from different places around the world. METHODS: The study used alignment free sequence descriptors for the representation of sequences and chemometric methods for analyzing clusters. RESULTS: Majority of genome sequences are clustered with respect to the virus type, but some of them are outliers. CONCLUSION: We indicate 71 sequences, which tend to belong to more than one cluster. Twit Text FOAVip Cluster Analysis of Coronavirus Sequences using Computational Sequence Descriptors: With Applications to SARS, MERS and SARS-CoV-2 (CoVID-19) ????Curr Comput Aided Drug Des http://www.kidney.de/pget.php?&tw=1&pmid=33530913 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33530913 #FOAvip English Wikipedia <ref>{{Cite pmid|33530913}}</ref> Cluster Analysis of Coronavirus Sequences using Computational Sequence Descriptors: With Applications to SARS, MERS and SARS-CoV-2 (CoVID-19) #MMPMID33530913 Vracko M; Basak SC; Dey T; Nandy A Curr Comput Aided Drug Des 2021[]; 17 (7): 936-945 PMID33530913show ga INTRODUCTION: Coronaviruses comprise a group of enveloped, positive-sense single-stranded RNA viruses that infect humans as well as a wide range of animals. The study was performed on a set of 573 sequences belonging to SARS, MERS and SARS-CoV-2 (CoVID-19) viruses. The sequences were represented with alignment-free sequence descriptors and analyzed with different chemometric methods: Euclidean/Mahalanobis distances, principal component analysis and self-organizing maps (Kohonen networks). We report the cluster structures of the data. The sequences are well-clustered regarding the type of virus; however, some of them show the tendency to belong to more than one virus type. BACKGROUND: This is a study of 573 genome sequences belonging to SARS, MERS and SARS-- CoV-2 (CoVID-19) coronaviruses. OBJECTIVES: The aim was to compare the virus sequences, which originate from different places around the world. METHODS: The study used alignment free sequence descriptors for the representation of sequences and chemometric methods for analyzing clusters. RESULTS: Majority of genome sequences are clustered with respect to the virus type, but some of them are outliers. CONCLUSION: We indicate 71 sequences, which tend to belong to more than one cluster. |*COVID-19[MESH] |*SARS-CoV-2[MESH] |Animals[MESH] |Cluster Analysis[MESH]Cluster Analysis of Coronavirus Sequences using Computational Sequence(epmc).pdf DeepDyve Pubget Overpricing