Nucleotide-level prediction of CircRNA-protein binding based on fully convolutional neural network.

ABSTRACT: Introduction: CircRNA-protein binding plays a critical role in complex biological activity and disease. Various deep learning-based algorithms have been proposed to identify CircRNA-protein binding sites. These methods predict whether the CircRNA sequence includes protein binding sites from the sequence level, and primarily concentrate on analysing the sequence specificity of CircRNA-protein binding. For model performance, these methods are unsatisfactory in accurately predicting motif sites that have special functions in gene expression. Methods: In this study, based on the deep learning models that implement pixel-level binary classification prediction in computer vision, we viewed the CircRNA-protein binding sites prediction as a nucleotide-level binary classification task

SUBMITTER: Shen Z 

PROVIDER: S-EPMC10587422 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature