Author: Karthi Balasubramanian; Nithin Nagaraj
Title: Automatic Identification of SARS Coronavirus using Compression-Complexity Measures Document date: 2020_3_27
ID: ljli6a2z_60
Snippet: . CC-BY-NC-ND 4.0 International license author/funder. It is made available under a The copyright holder for this preprint (which was not peer-reviewed) is the . https://doi.org/10.1101/2020.03.24.006007 doi: bioRxiv preprint Figure 4 : 95% confidence interval for mean d LZ (left) and d ET C (right) distance measures for the three viruses (pairwise) -SARS-CoV-2, BJ01 and Urbani. The distance between the two SARS-CoV-1 viruses is clearly the least.....
Document: . CC-BY-NC-ND 4.0 International license author/funder. It is made available under a The copyright holder for this preprint (which was not peer-reviewed) is the . https://doi.org/10.1101/2020.03.24.006007 doi: bioRxiv preprint Figure 4 : 95% confidence interval for mean d LZ (left) and d ET C (right) distance measures for the three viruses (pairwise) -SARS-CoV-2, BJ01 and Urbani. The distance between the two SARS-CoV-1 viruses is clearly the least for ETC, but not for LZ. Figure 5 : Effect of segment length on identification. Pairwise distances for the three viruses -SARS-CoV-2, BJ01 and Urbani computed using ETC and LZ based distance measures for a single randomly chosen contiguous segment of length 5000 bases (left) and 25 bases (right) from the nucleotide sequences. Only ETC correctly yields the least distance pair for the 2 SARS-CoV-1 viruses (BJ01 and Urbani) for both lengths.
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