Factorial Moments Analyses Show a Characteristic Length Scale in DNA Sequences

Rao, A. V. S. S. Narayana

doi:10.1103/physrevlett.84.1832

Cited by 42 publications

(23 citation statements)

References 20 publications

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“…The results obtained using this method demonstrated that a large number of known genetic texts contain sequences with latent periodicity of various lengths and various types. It is in agreement with the results of investigation of DNA sequences by integral mathematical methods and finding the long-range correlations (LRC) in DNA sequences [55][56][57][58][59][60][61][62][63][64][65][66][67][68]. a -Alpha platelet-derived growth factor receptor precursor [52] from Rattus norvegicus (1088 amino acids, PGDS_RAT in Swiss-prot).…”

Section: Discussionsupporting

confidence: 73%

Information decomposition method to analyze symbolical sequences

Korotkov

Korotkova²,

Kudryashov³

2003

Physics Letters A

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We developed a non-parametric method of Information Decomposition (ID) of a content of any symbolical sequence. The method is based on the calculation of Shannon mutual information between analyzed and artificial symbolical sequences, and allows the revealing of latent periodicity in any symbolical sequence. We show the stability of the ID method in the case of a large number of random letter changes in an analyzed symbolic sequence. We demonstrate the possibilities of the method, analyzing both poems, and DNA and protein sequences. In DNA and protein sequences we show the existence of many DNA and amino acid sequences with different types and lengths of latent periodicity. The possible origin of latent periodicity for different symbolical sequences is discussed.

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Section: Discussionsupporting

confidence: 73%

Information decomposition method to analyze symbolical sequences

Korotkov

Korotkova²,

Kudryashov³

2003

Physics Letters A

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“…The pioneer papers mainly focused on the controversial issue of whether long-range correlations are a property shared by both coding and non-coding sequences or are only present in non-coding sequences [2][3][4][5]. The results of more recent papers [6,7] yield the convincing conclusion that the former condition applies. However, some statistical aspects of the DNA sequences are still obscure, and it is not yet known to what an extent the dynamic approach to DNA sequences proposed by the authors of Ref.…”

Section: Introductionmentioning

confidence: 99%

Lévy scaling: The diffusion entropy analysis applied to DNA sequences

2002

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We address the problem of the statistical analysis of a time series generated by complex dynamics with a new method: the Diffusion Entropy Analysis (DEA) (Fractals, 9, 193 (2001)). This method is based on the evaluation of the Shannon entropy of the diffusion process generated by the time series imagined as a physical source of fluctuations, rather than on the measurement of the variance of this diffusion process, as done with the traditional methods. We compare the DEA to the traditional methods of scaling detection and we prove that the DEA is the only method that always yields the correct scaling value, if the scaling condition applies. Furthermore, DEA detects the real scaling of a time series without requiring any form of de-trending. We show that the joint use of DEA and variance method allows to assess whether a time series is characterized by Lévy or Gauss statistics. We apply the DEA to the study of DNA sequences, and we prove that their large-time scales are characterized by Lévy statistics, regardless of whether they are coding or non-coding sequences. We show that the DEA is a reliable technique and, at the same time, we use it to confirm the validity of the dynamic approach to the DNA sequences, proposed in earlier work. 03.65.Bz,

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“…Now, it has been widely used in the analysis of event by event correlations and fluctuations, such as the DNA sequence [29], the hadronic decay [30], and the spectra of complex networks [31], as it allows for a direct access to the dynamical fluctuations of the multiplicity with the function of dismissing the statistical fluctuations due to finite number of events [14]. While applied to the financial systems, it provides a way to analyze the intermittency or the self-similarity behaviors in the dynamics of distribution of the correlation coefficients, despite the limited financial data.…”

Section: Scaled Factorial Moment Methodsmentioning

confidence: 99%

On the Application of the Cross-Correlations in the Chinese Fund Market: Descriptive Properties and Scaling Behaviors

Deng

Cai

et al. 2011

Advs. Complex Syst.

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On the basis of the relative daily logarithmic returns of 88 different funds in the Chinese fund market (CFM) from June 2005 to October 2009, we construct the cross-correlation matrix of the CFM. It is shown that the logarithmic returns follow an exponential distribution, which is commonly shared by some emerging markets. We hereby analyze the statistical properties of the cross-correlation coefficients in different time periods, such as the distribution, the mean value, the standard deviation, the skewness and the kurtosis. By using the method of the scaled factorial moment, we observe the intermittence phenomenon in the distribution of the cross-correlation coefficients. Also by employing the random matrix theory (RMT), we find a few isolated large eigenvalues of the cross-correlation matrix, and the distribution of eigenvalues exhibits the power-law tails. Furthermore, we study the features of the correlation strength with a simple definition.

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Factorial Moments Analyses Show a Characteristic Length Scale in DNA Sequences

Cited by 42 publications

References 20 publications

Information decomposition method to analyze symbolical sequences

Information decomposition method to analyze symbolical sequences

Lévy scaling: The diffusion entropy analysis applied to DNA sequences

On the Application of the Cross-Correlations in the Chinese Fund Market: Descriptive Properties and Scaling Behaviors

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