Computational prediction of RNA m5C sites using sequences alone.
RNA modification plays a critical role in epigenetic regulations to alter a variety of biological processes. 5-methylcytosine (m5C) is one of the most typical modification involving mRNA export, translation efficiency and cell differentiation, and is known to be associated with human diseases including Alzheimer’s disease, autoimmune disease, cancer, and cardiovascular diseases. Identification of m5C on RNAs is critically responsible for understanding the mechanisms by which the RNA modification occurs and the regulation of how m5C causes its related diseases through epigenetic processes. However, large-scale experimental identification of m5C is laborious and time-consuming, accompanied by a problem with low sequencing quality. These problems lead to promotion of an efficient computational method that identifies 5mC to complement the experimental difficulties.