Autoregressive Modeling and Feature Analysis of DNA Sequences

Niranjan Chakravarthy, Andreas Spanias, L. D. Iasemidis, Konstantinos Tsakalis

Research output: Contribution to journalArticle

73 Citations (Scopus)

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 indicates 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 the proposed method is demonstrated.

Original languageEnglish (US)
Pages (from-to)13-28
Number of pages16
JournalEurasip Journal on Applied Signal Processing
Volume2004
Issue number1
DOIs
StatePublished - Jan 1 2004

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DNA sequences
String searching algorithms
Error analysis
Signal processing

Keywords

  • Autoregressive modeling
  • DNA
  • Feature analysis

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Hardware and Architecture
  • Signal Processing

Cite this

Autoregressive Modeling and Feature Analysis of DNA Sequences. / Chakravarthy, Niranjan; Spanias, Andreas; Iasemidis, L. D.; Tsakalis, Konstantinos.

In: Eurasip Journal on Applied Signal Processing, Vol. 2004, No. 1, 01.01.2004, p. 13-28.

Research output: Contribution to journalArticle

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