IPiDA-GCN: Identification of piRNA-disease associations based on Graph Convolutional Network.

ABSTRACT:

Motivation

Piwi-interacting RNAs (piRNAs) play a critical role in the progression of various diseases. Accurately identifying the associations between piRNAs and diseases is important for diagnosing and prognosticating diseases. Although some computational methods have been proposed to detect piRNA-disease associations, it is challenging for these methods to effectively capture nonlinear and complex relationships between piRNAs and diseases because of the limited training data and insufficient association representation.

Results

With the growth of piRNA-disease association data, it is possible to design a more complex machine learning method to solve this problem. In this study, we propose a computational method called iPiDA-GCN for piRNA-disease association identification b

SUBMITTER: Hou J 

PROVIDER: S-EPMC9662734 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature