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_47
Snippet: In summary, the approach presented in this paper is exploratory and hypotheses generating in nature. It does not confirm or reject any of the hypotheses we generated about the potential transmission and evolution pathways nor does it provide causal explanation for the patterns found. However, the purpose of our work is to provide an alternative view to the epidemic dynamics of the 2019-nCoV outbreak (and potential other outbreaks in the future) t.....
Document: In summary, the approach presented in this paper is exploratory and hypotheses generating in nature. It does not confirm or reject any of the hypotheses we generated about the potential transmission and evolution pathways nor does it provide causal explanation for the patterns found. However, the purpose of our work is to provide an alternative view to the epidemic dynamics of the 2019-nCoV outbreak (and potential other outbreaks in the future) that is hidden to state-of-the-art methods, and that may trigger geneticists and epidemiologists to look at pathways in epidemic outbreaks they would not normally be aware of.
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