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Bioinformatics
Article . 2011 . Peer-reviewed
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Bioinformatics
Article
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Bioinformatics
Article . 2011
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https://dx.doi.org/10.48550/ar...
Article . 2011
License: arXiv Non-Exclusive Distribution
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Topological entropy of DNA sequences

Authors: David Koslicki;

Topological entropy of DNA sequences

Abstract

Abstract Motivation: Topological entropy has been one of the most difficult to implement of all the entropy-theoretic notions. This is primarily due to finite sample effects and high-dimensionality problems. In particular, topological entropy has been implemented in previous literature to conclude that entropy of exons is higher than of introns, thus implying that exons are more ‘random’ than introns. Results: We define a new approximation to topological entropy free from the aforementioned difficulties. We compute its expected value and apply this definition to the intron and exon regions of the human genome to observe that as expected, the entropy of introns are significantly higher than that of exons. We also find that introns are less random than expected: their entropy is lower than the computed expected value. We also observe the perplexing phenomena that introns on chromosome Y have atypically low and bimodal entropy, possibly corresponding to random sequences (high entropy) and sequences that posses hidden structure or function (low entropy). Availability: A Mathematica implementation is available at http://www.math.psu.edu/koslicki/entropy.nb Contact: koslicki@math.psu.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Related Organizations
Keywords

Chromosomes, Human, Y, Statistical Mechanics (cond-mat.stat-mech), Genome, Human, Entropy, FOS: Physical sciences, DNA, Exons, Sequence Analysis, DNA, Quantitative Biology - Quantitative Methods, Introns, FOS: Biological sciences, Humans, Condensed Matter - Statistical Mechanics, Quantitative Methods (q-bio.QM)

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
57
Top 10%
Top 10%
Top 10%
Green
gold