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Identifying N (6)-methyladenosine sites in the Arabidopsis thaliana transcriptome.

N (6)-Methyladenosine (m(6)A) plays important roles in many biological processes. The knowledge of the distribution of m(6)A is helpful for understanding its regulatory roles. Although the experimental methods have been proposed to detect m(6)A, the resolutions of these methods are still unsatisfying especially for Arabidopsis thaliana. Benefitting from the experimental data, in the current work, a support vector machine-based method was proposed to identify m(6)A sites in A. thaliana transcriptome. The proposed method was validated on a benchmark dataset using jackknife test and was also validated by identifying strain-specific m(6)A sites in A. thaliana. The obtained predictive results indicate that the proposed method is quite promising. For the convenience of experimental biologists, an online webserver for the proposed method was built, which is freely available at https://lin.uestc.edu.cn/server/M6ATH . These results indicate that the proposed method holds a potential to become an elegant tool in identifying m(6)A site in A. thaliana.

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