MM-6mAPred: identifying DNA N6-methyladenine sites based on Markov model
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AbstractMotivation: Recent studies have shown that DNA N6-methyladenine (6mA) plays an important role in epigenetic modification of eukaryotic organisms. It has been found that 6mA is closely related to embryonic development, stress response and so on. Developing a new algorithm to quickly and accurately identify 6mA sites in genomes is important for explore their biological functions.
Results: In this paper, we proposed a new classification method called MM-6mAPred based on a Markov model which makes use of the transition probability between adjacent nucleotides to identify 6mA site. The sensitivity and specificity of our method are 89.32% and 90.11%, respectively. The overall accuracy of our method is 89.72%, which is 6.59% higher than that of the previous method i6mA-Pred. It indicated that, compared with the 41 nucleotide chemical properties used by i6mA-Pred, the transition probability between adjacent nucleotides can capture more discriminant sequence information.
Acceptance Date09/07/2019
All Author(s) ListPian C, Zhang GL, Li F, Fan XD
Journal nameBioinformatics
Year2020
Month1
Volume Number36
Issue Number2
PublisherOXFORD UNIV PRESS
Pages388 - 392
ISSN1367-4803
eISSN1460-2059
LanguagesEnglish-United Kingdom
Web of Science Subject CategoriesBiochemical Research Methods;Biotechnology & Applied Microbiology;Computer Science, Interdisciplinary Applications;Mathematical & Computational Biology;Statistics & Probability;Biochemistry & Molecular Biology;Biotechnology & Applied Microbiology;Computer Science;Mathematical & Computational Biology;Mathematics

Last updated on 2020-29-10 at 23:57