In the search for the low-complexity sequences in prokaryotic and eukaryotic genomes: how to derive a coherent picture from global and local entropy measures

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Paper discussing the search for the low-complexity sequences in prokaryotic and eukaryotic genomes and how to derive a coherent picture from global and local entropy measures.

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11 p.: ill.

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Acquisti, Claudia; Allegrini, Paolo; Bogani, Patrizia; Buiatti, Marcello, 1937-; Catanese, Elena; Fronzoni, Leone et al. 2003.

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Paper discussing the search for the low-complexity sequences in prokaryotic and eukaryotic genomes and how to derive a coherent picture from global and local entropy measures.

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11 p.: ill.

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This is the pre-print version of the paper.

Abstract: We investigate on a possible way to connect the presence of Low-Complexity Sequences (LCS) in DNA genomes and the nonstationary properties of base correlations. Under the hypothesis that these variations signal a change in the DNA function, we use a new technique, called Non-Stationarity Entropic Index (NSEI) method, and we prove that this technique is an efficient way to detect functional changes with respect to a random baseline. The remarkable aspect is that NSEI does not imply any training data or fitting parameter, the only arbitrarity being the choice of a marker in the sequence. We make this choice on the basis of biological information about LCS distributions in genomes. We show that there exists a correlation between changing the amount in LCS and the ration of long-to short-range correlation.

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  • arXiv: cond-mat/0310649

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  • 2003

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  • July 24, 2013, 1:20 p.m.

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  • April 2, 2014, 2:49 p.m.

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Acquisti, Claudia; Allegrini, Paolo; Bogani, Patrizia; Buiatti, Marcello, 1937-; Catanese, Elena; Fronzoni, Leone et al. In the search for the low-complexity sequences in prokaryotic and eukaryotic genomes: how to derive a coherent picture from global and local entropy measures, paper, 2003; (https://digital.library.unt.edu/ark:/67531/metadc174697/: accessed April 19, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; crediting UNT College of Arts and Sciences.

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