English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

A new approach to estimate the Shannon entropy of a long-range correlatedsequence is proposed. The entropy is written as the sum of two termscorresponding respectively to power-law (\emph{ordered}) and exponentially(\emph{disordered}) distributed blocks (clusters). The approach is illustratedon the 24 human chromosome sequences by taking the nucleotide composition asthe relevant information to be encoded/decoded. Interestingly, the nucleotidecomposition of the \emph{ordered} clusters is found, on the average, comparableto the one of the whole analyzed sequence, while that of the \emph{disordered}clusters fluctuates. From the information theory standpoint, this means thatthe power-law correlated clusters carry the same information of the wholeanalysed sequence. Furthermore, the fluctuations of the nucleotide compositionof the disordered clusters are linked to relevant biological properties, suchas segmental duplications and gene density.

Information Measures for Long-Range Correlated Sequences: the Case of the 24 Human Chromosome Sequences