Volume 8, Issue 3
Research on DNA Sequence Homology Based on Second Order Markov Model

Junyan Zhang & Chenhui Yang

Journal of Fiber Bioengineering & Informatics, 8 (2015), pp. 539-546.

Published online: 2015-08

Preview Purchase PDF 0 1801
Export citation
  • 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.

  • Keywords

DNA Sequence Homology Similarity Degree Second Order Markov Model

  • AMS Subject Headings

  • Copyright

COPYRIGHT: © Global Science Press

  • Email address
  • BibTex
  • RIS
  • TXT
@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
Copy to clipboard
The citation has been copied to your clipboard