Autoregressive modeling and feature analysis of DNA sequences
type: Item
instance of: scholarly article
title: Autoregressive modeling and feature analysis of DNA sequences
zbMATH Open document ID: 1066.92021
DOI: 10.1155/S111086570430925X
author: Niranjan Chakravarthy
published in: EURASIP Journal on Applied Signal Processing
publication date: 2005-05-03T00:00:00Z
review text: Summary: 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 the proposed method is demonstrated.
Mathematics Subject Classification ID: 92C40
Mathematics Subject Classification ID: 62M10
zbMATH DE Number: 2163803
MaRDI profile type: Publication
full work available at URL: s111086570430925x
OpenAlex ID: W1997730991
description: scientific article; zbMATH DE number 2163803