title: TargetM6A: Identifying N6-Methyladenosine Sites From RNA Sequences via Position-Specific Nucleotide Propensities and a Support Vector Machine.
abstract: As one of the most ubiquitous post-transcriptional modifications of RNA, N6-methyladenosine ( [Formula: see text]) plays an essential role in many vital biological processes. The identification of [Formula: see text] sites in RNAs is significantly important for both basic biomedical research and practical drug development. In this study, we designed a computational-based method, called TargetM6A, to rapidly and accurately target [Formula: see text] sites solely from the primary RNA sequences. Two new features, i.e., position-specific nucleotide/dinucleotide propensities (PSNP/PSDP), are introduced and combined with the traditional nucleotide composition (NC) feature to formulate RNA sequences. The extracted features are further optimized to obtain a much more compact and discriminative feature subset by applying an incremental feature selection (IFS) procedure. Based on the optimized feature subset, we trained TargetM6A on the training dataset with a support vector machine (SVM) as the prediction engine. We compared the proposed TargetM6A method with existing methods for predicting [Formula: see text] sites by performing stringent jackknife tests and independent validation tests on benchmark datasets. The experimental results show that the proposed TargetM6A method outperformed the existing methods for predicting [Formula: see text] sites and remarkably improved the prediction performances, with MCC = 0.526 and AUC = 0.818. We also provided a user-friendly web server for TargetM6A, which is publicly accessible for academic use at http://csbio.njust.edu.cn/bioinf/TargetM6A.
authors.forename: Guang-Qing
authors.initials: GQ
authors.lastname: Li
authors.forename: Zi
authors.initials: Z
authors.lastname: Liu
authors.forename: Hong-Bin
authors.initials: HB
authors.lastname: Shen
authors.forename: Dong-Jun
authors.initials: DJ
authors.lastname: Yu
mesh_terms: D000241:Adenosine / Q000031:analogs & derivatives* / Q000032:analysis / Q000737:chemistry; D019295:Computational Biology / Q000379:methods*; D012313:RNA / Q000032:analysis / Q000737:chemistry*; D012441:Saccharomyces cerevisiae / Q000235:genetics; D017423:Sequence Analysis, RNA / Q000379:methods*; D060388:Support Vector Machine
chemical_list: D012313:RNA; C010223:N-methyladenosine; D000241:Adenosine