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_16
Snippet: We perform an analysis of information token entropy and information token evenness in order to understand whether the virus evolution can be considered an open or a closed system. Therefore we assess both measures in an accumulated fashion for each progression step through the ordered nucleotide sequences. In a closed system the information token entropy should strive towards an equilibrium of maximum entropy and not feature any wave-like up and .....
Document: We perform an analysis of information token entropy and information token evenness in order to understand whether the virus evolution can be considered an open or a closed system. Therefore we assess both measures in an accumulated fashion for each progression step through the ordered nucleotide sequences. In a closed system the information token entropy should strive towards an equilibrium of maximum entropy and not feature any wave-like up and down patterns. If we observe wave-like patterns it means nucleotide sequences at later progression stages feature codon identifiers that have not been observed in earlier nucleotide sequences.
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