Predicting the potential human lncRNA–miRNA interactions based on graph convolution network with conditional random field
University of Science and Technology Liaoning · China University of Mining and Technology · +4 more institutions
Abstract
Long non-coding RNA (lncRNA) and microRNA (miRNA) are two typical types of non-coding RNAs (ncRNAs), their interaction plays an important regulatory role in many biological processes. Exploring the interactions between unknown lncRNA and miRNA can help us better understand the functional expression between lncRNA and miRNA. At present, the interactions between lncRNA and miRNA are mainly obtained through biological experiments, but such experiments are often time-consuming and labor-intensive, it is necessary to design a computational method that can predict the interactions between lncRNA and miRNA. In this paper, we propose a method based on graph convolutional neural (GCN) network and conditional random…
Citation impact
- FWCI
- 28.89
- Percentile
- 100%
- References
- 48
Authors
5- WWWenya Wang
University of Science and Technology Liaoning
- LZLi Zhang
China University of Mining and Technology
- JSJianqiang Sun
Linyi University
- QZQi ZhaoCorresponding
University of Science and Technology Liaoning
- JSJianwei ShuaiCorresponding
Xiamen University, Zhejiang Lab, University of Chinese Academy of Sciences
Topics & keywords
- Conditional random field
- Convolution (computer science)
- Computer science
- Field (mathematics)
- Graph
- Artificial intelligence
- Theoretical computer science
- Mathematics
- Decent work and economic growth