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Updated: Jun 13, 2026

A Bioinformatics Pipeline to Accurately and Efficiently Analyze the MicroRNA Transcriptomes in Plants
Published on: January 21, 2020
AthMethPre: a web server for the prediction and query of mRNA m6A sites in Arabidopsis thaliana
Shunian Xiang1, Zhangming Yan1, Ke Liu2
1MOE Key Laboratory of Bioinformatics, School of Life Sciences, Tsinghua University, Beijing 100084, P. R. China. sunzhr@mail.tsinghua.edu.cn.
Abstract:
N6-Methyladenosine (m6A) is the most prevalent and abundant modification in mRNA that has been linked to many key biological processes. High-throughput experiments have generated m6A-peaks across the transcriptome of A. thaliana, but the specific methylated sites were not assigned, which impedes the understanding of m6A functions in plants. Therefore, computational prediction of mRNA m6A sites becomes emergently important. Here, we present a method to predict the m6A sites for A. thaliana mRNA sequence(s). To predict the m6A sites of an mRNA sequence, we employed the support vector machine to build a classifier using the features of the positional flanking nucleotide sequence and position-independent k-mer nucleotide spectrum. Our method achieved good performance and was applied to a web server to provide service for the prediction of A. thaliana m6A sites. The server also provides a comprehensive database of predicted transcriptome-wide m6A sites and curated m6A-seq peaks from the literature for query and visualization. The AthMethPre web server is the first web server that provides a user-friendly tool for the prediction and query of A. thaliana mRNA m6A sites, which is freely accessible for public use at .
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