Prediction of Back-splicing sites for CircRNA formation based on convolutional neural networks.

ABSTRACT:

Background

Circular RNAs (CircRNAs) play critical roles in gene expression regulation and disease development. Understanding the regulation mechanism of CircRNAs formation can help reveal the role of CircRNAs in various biological processes mentioned above. Back-splicing is important for CircRNAs formation. Back-splicing sites prediction helps uncover the mysteries of CircRNAs formation. Several methods were proposed for back-splicing sites prediction or circRNA-realted prediction tasks. Model performance was constrained by poor feature learning and using ability.

Results

In this study, CircCNN was proposed to predict pre-mRNA back-splicing sites. Convolution neural network and batch normalization are the main parts of CircCNN. Experimental results on three datasets show tha

SUBMITTER: Shen Z 

PROVIDER: S-EPMC9373444 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature