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EURASIP Journal on Advances in Signal Processing
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Autoregressive Modeling and Feature Analysis of DNA Sequences

EURASIP Journal on Advances in Signal Processing volume 2004, Article number: 952689 (2004) Cite this article

Abstract

A parametric signal processing approach for DNA sequence analysis based on autoregressive (AR) modeling is presented. AR model residual errors and AR model parameters are used as features. The AR residual error analysis indicate a high specificity of coding DNA sequences, while AR feature-based analysis helps distinguish between coding and noncoding DNA sequences. An AR model-based string searching algorithm is also proposed. The effect of several types of numerical mapping rules in th proposed method is demonstrated.

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Affiliations

  1. Department of Electrical Engineering, Arizona State University, Tempe, AZ, 85287-5706, USA

    Niranjan Chakravarthy, A. Spanias & K. Tsakalis

  2. Harrington Department of Bioengineering, Arizona State University, Tempe, AZ, 85287-9709, USA

    L. D. Iasemidis

Authors
  1. Niranjan Chakravarthy
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  2. A. Spanias
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  3. L. D. Iasemidis
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  4. K. Tsakalis
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Correspondence to Niranjan Chakravarthy.

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Chakravarthy, N., Spanias, A., Iasemidis, L.D. et al. Autoregressive Modeling and Feature Analysis of DNA Sequences. EURASIP J. Adv. Signal Process. 2004, 952689 (2004). https://doi.org/10.1155/S111086570430925X

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  • DOI: https://doi.org/10.1155/S111086570430925X

Keywords and phrases

  • DNA
  • autoregressive modeling
  • feature analysis