PAI-SAE: Predicting Adenosine To Inosine Editing Sites Based On Hybrid Features By Using Spare Auto-Encoder

2nd International Symposium on Resource Exploration and Environmental Science

生态环境科学

Xiao, Xuan^1,2 ; Wang, Peng^1 ; Xu, Zhaochun^1 ; Qiu, Wangren^1,3 ; Fang, Xinzhu^1

Computer Department, Jing-De-Zhen Ceramic Institute, Jing-De-Zhen

333403, China^1

Gordon Life Science Institute, Boston

MA

02478, United States^2

Department of Computer Science, Bond Life Science Center, University of Missouri, Columbia

MO, United States^3

关键词: Biological functions;    Cross-covariance;    Drug development;    Hybrid features;    Jackknife tests;    Non-coding RNAs;    Post-transcriptional modification;    Transcriptomes;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/170/5/052018/pdf
DOI  :  10.1088/1755-1315/170/5/052018

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

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.