Author: Markus Luczak-Roesch
Title: Networks of information token recurrences derived from genomic sequences may reveal hidden patterns in epidemic outbreaks: A case study of the 2019-nCoV coronavirus. Document date: 2020_2_11
ID: kevrp8rg_3
Snippet: Our results show pathways of similarity between certain clusters of 2019-nCoV virus samples taken in different geographical locations, and indicate coronavirus cases that are candidates for further investigation into the human touch points of these patients in order to derive a detailed understanding of how the virus may have spread, and how and why it has genetically evolved. Our analysis provides a unique view to the dynamics of the 2019-nCoV c.....
Document: Our results show pathways of similarity between certain clusters of 2019-nCoV virus samples taken in different geographical locations, and indicate coronavirus cases that are candidates for further investigation into the human touch points of these patients in order to derive a detailed understanding of how the virus may have spread, and how and why it has genetically evolved. Our analysis provides a unique view to the dynamics of the 2019-nCoV coronavirus outbreak that complements knowledge obtained using other state-of-the-art methods such as Bayesian evolutionary analysis [9] .
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