Identifying the sequence specificities of circRNA-binding proteins based on a capsule network architecture
Open Access
- 7 January 2021
- journal article
- research article
- Published by Springer Science and Business Media LLC in BMC Bioinformatics
- Vol. 22 (1), 1-16
- https://doi.org/10.1186/s12859-020-03942-3
Abstract
Circular RNAs (circRNAs) are widely expressed in cells and tissues and are involved in biological processes and human diseases. Recent studies have demonstrated that circRNAs can interact with RNA-binding proteins (RBPs), which is considered an important aspect for investigating the function of circRNAs. In this study, we design a slight variant of the capsule network, called circRB, to identify the sequence specificities of circRNAs binding to RBPs. In this model, the sequence features of circRNAs are extracted by convolution operations, and then, two dynamic routing algorithms in a capsule network are employed to discriminate between different binding sites by analysing the convolution features of binding sites. The experimental results show that the circRB method outperforms the existing computational methods. Afterwards, the trained models are applied to detect the sequence motifs on the seven circRNA-RBP bound sequence datasets and matched to known human RNA motifs. Some motifs on circular RNAs overlap with those on linear RNAs. Finally, we also predict binding sites on the reported full-length sequences of circRNAs interacting with RBPs, attempting to assist current studies. We hope that our model will contribute to better understanding the mechanisms of the interactions between RBPs and circRNAs. In view of the poor studies about the sequence specificities of circRNA-binding proteins, we designed a classification framework called circRB based on the capsule network. The results show that the circRB method is an effective method, and it achieves higher prediction accuracy than other methods.Keywords
Funding Information
- National Natural Science Foundation of China (61672334, 61972451, 61902230)
- Fundamental Research Funds for the Central Universities (No. GK201901010)
This publication has 46 references indexed in Scilit:
- circRNA Biogenesis Competes with Pre-mRNA SplicingMolecular Cell, 2014
- starBase v2.0: decoding miRNA-ceRNA, miRNA-ncRNA and protein–RNA interaction networks from large-scale CLIP-Seq dataNucleic Acids Research, 2013
- The Expanding Repertoire of Circular RNAsMolecular Therapy, 2013
- Circular RNAs: splicing’s enigma variationsThe EMBO Journal, 2013
- Predicting RNA-Protein Interactions Using Only Sequence InformationBMC Bioinformatics, 2011
- iCLIP reveals the function of hnRNP particles in splicing at individual nucleotide resolutionNature Structural & Molecular Biology, 2010
- Transcriptome-wide Identification of RNA-Binding Protein and MicroRNA Target Sites by PAR-CLIPCell, 2010
- HITS-CLIP yields genome-wide insights into brain alternative RNA processingNature, 2008
- The use of the area under the ROC curve in the evaluation of machine learning algorithmsPattern Recognition, 1997
- Viroids are single-stranded covalently closed circular RNA molecules existing as highly base-paired rod-like structures.Proceedings of the National Academy of Sciences of the United States of America, 1976