Author: Karthi Balasubramanian; Nithin Nagaraj
Title: Automatic Identification of SARS Coronavirus using Compression-Complexity Measures Document date: 2020_3_27
ID: ljli6a2z_44
Snippet: In our experiment, the sequences are converted to three independent sets of 0-1 sequences (by using the three methods listed in Table 2 ) and the LZ and ETC distances are independently calculated for all three sets. The average values of these are taken as the distance between the two sequences. In order to automatically identify the SARS viruses, the two SARS coronaviruses (Urbani and BJ01) should have the minimum distance (in complexities) as c.....
Document: In our experiment, the sequences are converted to three independent sets of 0-1 sequences (by using the three methods listed in Table 2 ) and the LZ and ETC distances are independently calculated for all three sets. The average values of these are taken as the distance between the two sequences. In order to automatically identify the SARS viruses, the two SARS coronaviruses (Urbani and BJ01) should have the minimum distance (in complexities) as compared with the distance between the avian strain and any of the SARS coronaviruses (Urbani and BJ01). This method of identification can be easily extended if there are more than 3 sequences. The mean pairwise distances (and standard deviations) are reported in Table 3 . As it can be seen, both LZ and ETC based distance measures yield the least value for the SARS-CoV-1 virus pair. 5 AB is the new sequence obtained by simply concatenating sequence B at the end of sequence A. d(B, A) . The triangle inequality is also likely to hold. 7 Here d(·, ·) could be either dET C or dLZ .
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