Wavelet-based multiscale filtering of genomic data

Mohamed Nounou, Hazem Nounou, Nader Meskin, Aniruddha Datta

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Measured biological data are a rich source of information about the biological phenomena they represent. For example, time-series genomic or metabolic microarray data can be used to construct dynamic genetic regulatory network models, which can be used to better understand the biological system and to design intervention strategies to cure or manage major diseases. Unfortunately, biological measurements are usually highly contaminated with errors that mask the important features in the data. Therefore, these noisy measurements need to be filtered to enhance their usefulness in practice. Wavelet-based multiscale filtering has been shown to be a powerful data analysis and denoising tool. In this work, different batch as well as online multiscale filtering techniques are used to filter biological data contaminated with white noise. The performances of these multiscale filtering techniques are demonstrated and compared to those of some conventional low pass filters using simulated time series metabolic data. The results of this comparative study show that significant improvement can be achieved using multiscale filtering over conventional filtering methods.

Original languageEnglish
Title of host publicationProceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012
Pages804-809
Number of pages6
DOIs
Publication statusPublished - 2012
Event2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012 - Istanbul, Turkey
Duration: 26 Aug 201229 Aug 2012

Other

Other2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012
CountryTurkey
CityIstanbul
Period26/8/1229/8/12

Fingerprint

Time series
Low pass filters
Biological systems
White noise
Microarrays
Masks

Keywords

  • Genomic data
  • Multiscale filtering
  • Wavelets

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software

Cite this

Nounou, M., Nounou, H., Meskin, N., & Datta, A. (2012). Wavelet-based multiscale filtering of genomic data. In Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012 (pp. 804-809). [6425661] https://doi.org/10.1109/ASONAM.2012.146

Wavelet-based multiscale filtering of genomic data. / Nounou, Mohamed; Nounou, Hazem; Meskin, Nader; Datta, Aniruddha.

Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012. 2012. p. 804-809 6425661.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Nounou, M, Nounou, H, Meskin, N & Datta, A 2012, Wavelet-based multiscale filtering of genomic data. in Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012., 6425661, pp. 804-809, 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012, Istanbul, Turkey, 26/8/12. https://doi.org/10.1109/ASONAM.2012.146
Nounou M, Nounou H, Meskin N, Datta A. Wavelet-based multiscale filtering of genomic data. In Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012. 2012. p. 804-809. 6425661 https://doi.org/10.1109/ASONAM.2012.146
Nounou, Mohamed ; Nounou, Hazem ; Meskin, Nader ; Datta, Aniruddha. / Wavelet-based multiscale filtering of genomic data. Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012. 2012. pp. 804-809
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