m5CPred-SVM: a novel method for predicting m5C sites of RNA.

Journal: BMC bioinformatics
Published Date:

Abstract

BACKGROUND: As one of the most common post-transcriptional modifications (PTCM) in RNA, 5-cytosine-methylation plays important roles in many biological functions such as RNA metabolism and cell fate decision. Through accurate identification of 5-methylcytosine (m5C) sites on RNA, researchers can better understand the exact role of 5-cytosine-methylation in these biological functions. In recent years, computational methods of predicting m5C sites have attracted lots of interests because of its efficiency and low-cost. However, both the accuracy and efficiency of these methods are not satisfactory yet and need further improvement.

Authors

  • Xiao Chen
  • Yi Xiong
    Departement of Medical Oncology, Lung Cancer and Gastrointestinal Unit, Hunan Cancer Hospital/Affiliated Cancer Hospital of Xiangya School of Medicine, Changsha 410013, China.
  • Yinbo Liu
    School of Sciences, Anhui Agricultural University, Hefei, 230036, Anhui, China.
  • Yuqing Chen
    School of Clinical Medicine, University of Cambridge, Cambridge CB2 0SP, United Kingdom.
  • Shoudong Bi
    School of Sciences, Anhui Agricultural University, Hefei, 230036, Anhui, China. bishoudong@163.com.
  • Xiaolei Zhu
    School of Information and Artificial Intelligence, Anhui Agricultural University, Hefei, Anhui, China.