A support vector machine based-method is proposed to identify m(6)A sites in Saccharomyces cerevisiae genome. In this model, RNA sequences are encoded by their nucleotide chemical property and accumulated nucleotide frequency information. It is observed in the jackknife test that the accuracy achieved by the proposed model in identifying the m(6)A site was 78.15%.
Department of Physics, School of Sciences, and Center for Genomics and Computational Biology, Hebei United University, Tangshan, China; Department of Computer Science, Virginia Tech, Blacksburg, VA, USA; Key Laboratory for Neuro-Information of Ministry of Education, Center of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
m6Apred funding source(s)
This work was supported by National Nature Scientific Foundation of China (Nos. 61100092 and 61202256), Nature Scientific Foundation of Hebei Province (No. C2013209105), Program for the Top Young Innovative Talents of Higher Learning Institutions of Hebei Province (No. BJ2014028).