Bioinformatics · 2019 · 76 citations · 17 references
Life SciencesBioinformaticsBiologyComputational BiologyEpigeneticsGenomicsDna MethylationSequence Similarity SearchChemical PropertiesEpigenetic Base ModificationEpigenetic ClassificationEpigenetic RegulationMethylation Site PredictionTransition Probability AnalysisTransition Probability MatrixTransition Probability Models
MOTIVATION: 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. AVAILABILITY AND IMPLEMENTATION: The web server of MM-6mAPred is freely accessible at http://www.insect-genome.com/MM-6mAPred/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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