Research on DNA Sequence Homology Based on Second Order Markov Model
DOI:
10.3993/jfbim00154
Journal of Fiber Bioengineering & Informatics, 8 (2015), pp. 539-546.
Published online: 2015-08
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@Article{JFBI-8-539,
author = {},
title = {Research on DNA Sequence Homology Based on Second Order Markov Model},
journal = {Journal of Fiber Bioengineering and Informatics},
year = {2015},
volume = {8},
number = {3},
pages = {539--546},
abstract = {DNA sequence homology is a critical and fundamental problem in bioinformatics. In this paper, we
solve this problem by use of the second order Markov modal instead of traditional sequence alignment
because DNA character sequence meets the Markov properties. Hence, the characteristics of DNA
sequences are represented by using their two-step transition probabilities matrices. The similarity degree
measurement between two different DNA sequences is defined. Our DSHM algorithm is put forward
which is implemented by MyEclipse. The contrast experiments are done between DSHM and other two
methods. The experimental results show that DSHM algorithm can determine DNA sequence homology
correctly in the more effective way.},
issn = {2617-8699},
doi = {https://doi.org/10.3993/jfbim00154},
url = {http://global-sci.org/intro/article_detail/jfbi/4735.html}
}
TY - JOUR
T1 - Research on DNA Sequence Homology Based on Second Order Markov Model
JO - Journal of Fiber Bioengineering and Informatics
VL - 3
SP - 539
EP - 546
PY - 2015
DA - 2015/08
SN - 8
DO - http://doi.org/10.3993/jfbim00154
UR - https://global-sci.org/intro/article_detail/jfbi/4735.html
KW - DNA Sequence Homology
KW - Similarity Degree
KW - Second Order Markov Model
AB - DNA sequence homology is a critical and fundamental problem in bioinformatics. In this paper, we
solve this problem by use of the second order Markov modal instead of traditional sequence alignment
because DNA character sequence meets the Markov properties. Hence, the characteristics of DNA
sequences are represented by using their two-step transition probabilities matrices. The similarity degree
measurement between two different DNA sequences is defined. Our DSHM algorithm is put forward
which is implemented by MyEclipse. The contrast experiments are done between DSHM and other two
methods. The experimental results show that DSHM algorithm can determine DNA sequence homology
correctly in the more effective way.
Junyan Zhang & Chenhui Yang. (2019). Research on DNA Sequence Homology Based on Second Order Markov Model.
Journal of Fiber Bioengineering and Informatics. 8 (3).
539-546.
doi:10.3993/jfbim00154
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