| Description: | This article discusses Lévy scaling and the diffusion entropy analysis applied to DNA sequences. Abstract: We address the problem of the statistical analysis of a time series generated by complex dynamics with the diffusion entropy analysis (DEA) [N. Scafetta, P. Hamilton, and P. Grigolini, 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 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 detrending. 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 prove that their large-time scales are characterized by Lévy statistics, regardless of whether they are coding or noncoding 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. |
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| Creator(s): | |
| Creation Date: | September 20, 2002 |
| Partner(s): |
UNT College of Arts and Sciences
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| Collection(s): |
UNT Scholarly Works
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| Usage: |
Total Uses: 32
Past 30 days: 0
Yesterday: 0
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| Creator (Author): |
Scafetta, Nicola
Duke University; University of North Texas |
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| Creator (Author): |
Latora, Vito
Universitá di Catania and INFN |
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| Creator (Author): |
Grigolini, Paolo
University of North Texas; Universitá di Pisa and INFM; Istituto di Biofisica CNR |
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| Publisher Info: |
Publisher Name: American Physical Society
Place of Publication: [College Park, Maryland]
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| Date(s): |
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| Description: | This article discusses Lévy scaling and the diffusion entropy analysis applied to DNA sequences. Abstract: We address the problem of the statistical analysis of a time series generated by complex dynamics with the diffusion entropy analysis (DEA) [N. Scafetta, P. Hamilton, and P. Grigolini, 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 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 detrending. 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 prove that their large-time scales are characterized by Lévy statistics, regardless of whether they are coding or noncoding 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. |
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| Degree: |
Department:
Physics
Department:
Center for Nonlinear Science
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| Note: |
Copyright 2002 American Physical Society. The following article appeared in Physical Review E, 66:3; http://pre.aps.org/abstract/PRE/v66/i3/e031906 |
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| Physical Description: |
15 p. |
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| Keyword(s): | diffusion entropy analyses | Lévy scaling | DNA sequences | |
| Source: | Physical Review E, 2002, College Park: American Physical Society | |
| Partner: |
UNT College of Arts and Sciences
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| Collection: |
UNT Scholarly Works
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| Resource Type: | Article | |
| Format: | Text | |
| Rights: |
Access:
Public
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| Citation: |
Publication Title: Physical Review E
Volume: 66
Issue: 3
Pages: 15
Peer Reviewed: Yes
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