PAI-SAE: Predicting Adenosine to Inosine Editing Sites Based on Hybrid Features by Using Spare Auto-Encoder

Abstract

Adenosine-to-inosine RNA editing is an important post-transcriptional modification, which converts adenosines to inosines in both coding and noncoding RNA transcripts. Therefore, this modification can result in the diversification of the transcriptome. It is significant to accurately identify adenosine-to-inosine editing sites for further understanding their biological functions. Given an uncharacterized RNA sequence that contains many adenosine resides, can we identify which one of them can be converted to inosine, and which one cannot? To meet the increasingly high demand form most experimental scientists working in the area of drug development, we have developed a new predictor called PAI-SAE by hybrid features combining with dinucleotide-based auto-cross covariance (DACC), pseudo dinucleotide composition (Pse DNC) and nucleotide density, followed by a spare auto-encoder model. It has been observed via rigorous jackknife test that the predictor PAI-SAE is superior to others in this area.