ArticleScientific reports2013
Information measure for long-range correlated sequences: the case of the 24 human chromosomes.
Article in Scientific reports, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- DNA Sequence Perplexity Reveals Evolutionarily Conserved Patterns in cis-Regulatory Regions Across Diverse Species.Biochemical genetics · 2026Article
- Long-Range Dependence in Financial Markets: A Moving Average Cluster Entropy Approach.Entropy (Basel, Switzerland) · 2020Article
- Some comments on Bitcoin market (in)efficiency.PloS one · 2019Article
- Estimating the anomalous diffusion exponent for single particle tracking data with measurement errors - An alternative approach.Scientific reports · 2015Article
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1 author.
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Abstract
A new approach to estimate the Shannon entropy of a long-range correlated sequence is proposed. The entropy is written as the sum of two terms corresponding respectively to power-law (ordered) and exponentially (disordered) distributed blocks (clusters). The approach is illustrated on the 24 human chromosome sequences by taking the nucleotide composition as the relevant information to be encoded/decoded. Interestingly, the nucleotide composition of the ordered clusters is found, on the average, comparable to the one of the whole analyzed sequence, while that of the disordered clusters fluctuates. From the information theory standpoint, this means that the power-law correlated clusters carry the same information of the whole analysed sequence. Furthermore, the fluctuations of the nucleotide composition of the disordered clusters are linked to relevant biological properties, such as segmental duplications and gene density.
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