Literature DB >> 17334986

Linear regression model of DNA sequences and its application.

Qi Dai1, Xiao-Qing Liu, Tian-Ming Wang, Damir Vukicevic.   

Abstract

We constructed six new models to analyze the DNA sequences. First, we regarded a DNA primary sequence as a random process in t and gave three ways to define nucleotides' random distribution functions. We extracted some parameters from the linear model and analyzed the changes of the nucleotides' distributions. In order to facilitate the comparison of DNA sequences, we proposed two ways to measure their similarities. Finally, we compared the six models by analyzing the similarities of the DNA primary sequences presented in Table 1 and selected the optimal one.

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Year:  2007        PMID: 17334986     DOI: 10.1002/jcc.20556

Source DB:  PubMed          Journal:  J Comput Chem        ISSN: 0192-8651            Impact factor:   3.376


  3 in total

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Authors:  Miguel A Fuertes; José R Rodrigo; Carlos Alonso
Journal:  J Mol Evol       Date:  2019-02-28       Impact factor: 2.395

2.  Empirical relationship between intra-purine and intra-pyrimidine differences in conserved gene sequences.

Authors:  Ashesh Nandy
Journal:  PLoS One       Date:  2009-08-28       Impact factor: 3.240

3.  Using Gaussian model to improve biological sequence comparison.

Authors:  Qi Dai; Xiaoqing Liu; Lihua Li; Yuhua Yao; Bin Han; Lei Zhu
Journal:  J Comput Chem       Date:  2010-01-30       Impact factor: 3.376

  3 in total

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