Analysis of Molecular Dynamic Simulations Using Wavelet-Based Techniques

A. Abdel-Hafiez

doi:doi:10.11648/j.ajpa.20150304.13

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Analysis of Molecular Dynamic Simulations Using Wavelet-Based Techniques

A. Abdel-Hafiez

Published in American Journal of Physics and Applications (Volume 3, Issue 4)

Received: 9 June 2015 Accepted: 26 June 2015 Published: 7 July 2015

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Abstract

In this paper, I focus on describe, calculate and analyze of molecular dynamic (MD) simulations using wavelet transform (WT) techniques by analogy with its use in signal and image processing, so that I would like to talk about the theoretical background wavelet transform methods, including what properties they have, their common types, and how to operate them. Secondly, I would introduce the continuous wavelet transform, which is especially well-suited for time course data such as molecular dynamics simulations., the WT permits filtering out the high-frequency noise without completely omitting the high-frequency phenomena whose contribution is crucial in cases where the dynamics is localized in frequency and time. Medical applications could be studied in which biomedical related research requires lots of mathematical and engineering techniques to analyze data. The WT is observed to excel in reconstructing the original signal by a subset of the basis used in the analysis and in identifying the occurrence of rare phenomena by examining the wavelet energies at high-resolution levels.

Published in	American Journal of Physics and Applications (Volume 3, Issue 4)
DOI	10.11648/j.ajpa.20150304.13
Page(s)	131-137
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Molecular Dynamics, Wavelet Techniques, Some Applications

References

[1]	R.X. Gao, R. Yan, Wavelets: Theory and Applications for Manufacturing, Springer, 2010
[2]	M. Akay et al. Time Frequency and Wavelets in Biomedical Signal Processing, Wiley-IEEE Press, 1997
[3]	L. Cohen, "Time-frequency distributions-A review," Proc. IEEE, vol. 77, pp.941-981, 1989.
[4]	L. Cohen, Time-Frequency Signal Analysis. Englewood Cliffs, NJ: Prentice Hall, 1995.
[5]	T.C.M. Claasen and W.F.G. Mecklenbrauker, "The Wigner distribution-A tool for time-frequency signal analysis-Part I: Continuous-time signals," Philips J. Res., vol. 35, pp. 217-250, 1980.
[6]	T.C.M. Claasen and W.F.G. Mecklenbrauker, "The Wigner distribution-A tool for time-frequency signal analysis-Part II: Discrete time signals," Philips J. Res., vol. 35, pp. 276-300, 1980.
[7]	A. Nayak, R.J. Roy, and A. Sharma,"Time-frequency spectral representation of the EEG as an aid in the detection of depth of anesthesia," Ann. Biomed. Eng., vol. 22, pp. 501-513,1994.
[8]	T. C.M. Claasen and W.F.G. Mecklenbrauker, "The Wigner distribution-A tool for time-frequency signal analysis-Part III: Relations with other time-frequency signal transformations," Philips J. Res., vol. 35, pp. 372-389, 1980.
[9]	W. J. Williams and T. H. Sang, "Adaptive RID kernels which minimize time-frequency uncertainty," IEEE Int. SY111p. Time-Frequency and Time-Scale Analysis, pp. 96-99, 1994.
[10]	W.J. Williams, "Time-frequency analysis of biological signals," IEEE Int.Conf. Acoust. Speech, Signal Proc., vol. I, pp. 83-~6, 1993.
[11]	C.S. Zheng, W.J. Williams, and J.C. Sackellares, "RID time-frequency analysis of median filters and lowpass filters in reducing EMG artifacts in EEGrecording," Proc. IEEE Int. Con. Eng. Med. Bioi., vol. 15, pt. I, pp. 350-351,1993.
[12]	Beck DAC, Jonsson AL, Schaeffer RD, Scott KA, Day R, Toofanny RD, Alonso DO, Daggett V. Dynameomics: mass annotation of protein dynamics and unfolding in water by high-throughput atomistic molecular dynamics simulations. Protein: Engineering, Design and Selection. 2008; 21:353.
[13]	van der Kamp MW, Schaeffer RD, Jonsson AL, Scouras AD, Simms AM, Toofanny RD, Benson NC, Anderson PC, Merkley ED, Rysavy S, Bromley D, Beck DAC, Daggett V. Dynameomics: a comprehensive database of protein dynamics. Structure. 2010; 18(4):423. [PubMed: 20399180]
[14]	Shaw, DE.; Dror, RO.; Salmon, JK.; Grossman, JP.; Mackenzie, KM.; Bank, JA.; Young, C.; Deneroff, MM.; Batson, B.; Bowers, KJ.; Chow, E.; Eastwood, MP.; Ierardi, DJ.; Klepeis, JL.; Kuskin, JS.; Larson, RH.; Lindorff-Larsen, K.; Maragakis, P.; Moraes, MA.; Piana, S.; Shan, Y.; Towles, B. Proceedings of the Conference on High Performance Computing, Networking, Storage and Analysis (SC09). New York, NY, USA: Association of Computing Machinery; 2009. Millisecond-Scale molecular dynamics simulations on Anton.
[15]	Dror RO, Jensen M, Borhani DW, Shaw DE. Exploring atomic resolution physiology on a femtosecond to millisecond timescale using molecular dynamics simulations. Journal of General Physiology. 2010; 135:555. [PubMed: 20513757]
[16]	Miao L, Schulton K. Probing a structural model of the nuclear pore complex channel through molecular dynamics. Biophysical Journal. 2010; 98:1658. [PubMed: 20409487]
[17]	Lindahl E, Samsom MSP. Membrane proteins: molecular dynamics. Current Opinions in Structural Biology. 2008; 18:425.
[18]	Day R, Daggett V. All-atom simulations of protein folding and unfolding. Advances in Protein Chemistry. 2003; 66:373. [PubMed: 14631823]
[19]	StephaneMallat. A Wavelet Tour Of Signal Processing. Academic Press, 1998.
[20]	StephaneMallat and SifenZhong. Characterization of signals from multiscale edges. IEEE TRANSACTION ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 14(7):23, July 1992.
[21]	Mauro Barni. Document and Image Compression. CRS Press, Taylor and Francis Group, 2006.
[22]	Kehl C, Simms AM, Toofanny RD, Daggett V, Fersht A. Dynameomics: a multi-dimensional analysis-optimized database for dynamic protein data. Protein: Design, Engineering, and Selection. 2008; 21:379.
[23]	Simms AM, Toofanny RD, Kehl C, Benson NC, Daggett V. Dynameomics: design of a computational lab workflow and scientific data repository for protein simulations. Protein: Design, Engineering, and Selection. 2008; 21:369.

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A. Abdel-Hafiez. (2015). Analysis of Molecular Dynamic Simulations Using Wavelet-Based Techniques. American Journal of Physics and Applications, 3(4), 131-137. https://doi.org/10.11648/j.ajpa.20150304.13

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ACS Style

A. Abdel-Hafiez. Analysis of Molecular Dynamic Simulations Using Wavelet-Based Techniques. Am. J. Phys. Appl. 2015, 3(4), 131-137. doi: 10.11648/j.ajpa.20150304.13

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A. Abdel-Hafiez. Analysis of Molecular Dynamic Simulations Using Wavelet-Based Techniques. Am J Phys Appl. 2015;3(4):131-137. doi: 10.11648/j.ajpa.20150304.13

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@article{10.11648/j.ajpa.20150304.13,
  author = {A. Abdel-Hafiez},
  title = {Analysis of Molecular Dynamic Simulations Using Wavelet-Based Techniques},
  journal = {American Journal of Physics and Applications},
  volume = {3},
  number = {4},
  pages = {131-137},
  doi = {10.11648/j.ajpa.20150304.13},
  url = {https://doi.org/10.11648/j.ajpa.20150304.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajpa.20150304.13},
  abstract = {In this paper, I focus on describe, calculate and analyze of molecular dynamic (MD) simulations using wavelet transform (WT) techniques by analogy with its use in signal and image processing, so that I would like to talk about the theoretical background wavelet transform methods, including what properties they have, their common types, and how to operate them. Secondly, I would introduce the continuous wavelet transform, which is especially well-suited for time course data such as molecular dynamics simulations., the WT permits filtering out the high-frequency noise without completely omitting the high-frequency phenomena whose contribution is crucial in cases where the dynamics is localized in frequency and time. Medical applications could be studied in which biomedical related research requires lots of mathematical and engineering techniques to analyze data. The WT is observed to excel in reconstructing the original signal by a subset of the basis used in the analysis and in identifying the occurrence of rare phenomena by examining the wavelet energies at high-resolution levels.},
 year = {2015}
}

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TY  - JOUR
T1  - Analysis of Molecular Dynamic Simulations Using Wavelet-Based Techniques
AU  - A. Abdel-Hafiez
Y1  - 2015/07/07
PY  - 2015
N1  - https://doi.org/10.11648/j.ajpa.20150304.13
DO  - 10.11648/j.ajpa.20150304.13
T2  - American Journal of Physics and Applications
JF  - American Journal of Physics and Applications
JO  - American Journal of Physics and Applications
SP  - 131
EP  - 137
PB  - Science Publishing Group
SN  - 2330-4308
UR  - https://doi.org/10.11648/j.ajpa.20150304.13
AB  - In this paper, I focus on describe, calculate and analyze of molecular dynamic (MD) simulations using wavelet transform (WT) techniques by analogy with its use in signal and image processing, so that I would like to talk about the theoretical background wavelet transform methods, including what properties they have, their common types, and how to operate them. Secondly, I would introduce the continuous wavelet transform, which is especially well-suited for time course data such as molecular dynamics simulations., the WT permits filtering out the high-frequency noise without completely omitting the high-frequency phenomena whose contribution is crucial in cases where the dynamics is localized in frequency and time. Medical applications could be studied in which biomedical related research requires lots of mathematical and engineering techniques to analyze data. The WT is observed to excel in reconstructing the original signal by a subset of the basis used in the analysis and in identifying the occurrence of rare phenomena by examining the wavelet energies at high-resolution levels.
VL  - 3
IS  - 4
ER  -

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Author Information

A. Abdel-Hafiez

Experimental nuclear physics Department, Nuclear research center, AEA, Cairo, Egypt

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A. Abdel-Hafiez. (2015). Analysis of Molecular Dynamic Simulations Using Wavelet-Based Techniques. American Journal of Physics and Applications, 3(4), 131-137. https://doi.org/10.11648/j.ajpa.20150304.13

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ACS Style

A. Abdel-Hafiez. Analysis of Molecular Dynamic Simulations Using Wavelet-Based Techniques. Am. J. Phys. Appl. 2015, 3(4), 131-137. doi: 10.11648/j.ajpa.20150304.13

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AMA Style

A. Abdel-Hafiez. Analysis of Molecular Dynamic Simulations Using Wavelet-Based Techniques. Am J Phys Appl. 2015;3(4):131-137. doi: 10.11648/j.ajpa.20150304.13

Copy | Download

@article{10.11648/j.ajpa.20150304.13,
  author = {A. Abdel-Hafiez},
  title = {Analysis of Molecular Dynamic Simulations Using Wavelet-Based Techniques},
  journal = {American Journal of Physics and Applications},
  volume = {3},
  number = {4},
  pages = {131-137},
  doi = {10.11648/j.ajpa.20150304.13},
  url = {https://doi.org/10.11648/j.ajpa.20150304.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajpa.20150304.13},
  abstract = {In this paper, I focus on describe, calculate and analyze of molecular dynamic (MD) simulations using wavelet transform (WT) techniques by analogy with its use in signal and image processing, so that I would like to talk about the theoretical background wavelet transform methods, including what properties they have, their common types, and how to operate them. Secondly, I would introduce the continuous wavelet transform, which is especially well-suited for time course data such as molecular dynamics simulations., the WT permits filtering out the high-frequency noise without completely omitting the high-frequency phenomena whose contribution is crucial in cases where the dynamics is localized in frequency and time. Medical applications could be studied in which biomedical related research requires lots of mathematical and engineering techniques to analyze data. The WT is observed to excel in reconstructing the original signal by a subset of the basis used in the analysis and in identifying the occurrence of rare phenomena by examining the wavelet energies at high-resolution levels.},
 year = {2015}
}

Copy | Download

TY  - JOUR
T1  - Analysis of Molecular Dynamic Simulations Using Wavelet-Based Techniques
AU  - A. Abdel-Hafiez
Y1  - 2015/07/07
PY  - 2015
N1  - https://doi.org/10.11648/j.ajpa.20150304.13
DO  - 10.11648/j.ajpa.20150304.13
T2  - American Journal of Physics and Applications
JF  - American Journal of Physics and Applications
JO  - American Journal of Physics and Applications
SP  - 131
EP  - 137
PB  - Science Publishing Group
SN  - 2330-4308
UR  - https://doi.org/10.11648/j.ajpa.20150304.13
AB  - In this paper, I focus on describe, calculate and analyze of molecular dynamic (MD) simulations using wavelet transform (WT) techniques by analogy with its use in signal and image processing, so that I would like to talk about the theoretical background wavelet transform methods, including what properties they have, their common types, and how to operate them. Secondly, I would introduce the continuous wavelet transform, which is especially well-suited for time course data such as molecular dynamics simulations., the WT permits filtering out the high-frequency noise without completely omitting the high-frequency phenomena whose contribution is crucial in cases where the dynamics is localized in frequency and time. Medical applications could be studied in which biomedical related research requires lots of mathematical and engineering techniques to analyze data. The WT is observed to excel in reconstructing the original signal by a subset of the basis used in the analysis and in identifying the occurrence of rare phenomena by examining the wavelet energies at high-resolution levels.
VL  - 3
IS  - 4
ER  -

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