LncRNA-disease association prediction method based on heterogeneous information completion and convolutional neural network

TL;DR

This paper introduces HCNNLDA, a deep learning model combining heterogeneous network embedding and CNN to accurately predict lncRNA-disease associations, outperforming existing methods and demonstrating effectiveness in identifying novel associations.

Contribution

The paper presents a novel deep learning framework that integrates heterogeneous biological data with CNN for improved LDA prediction accuracy.

Findings

Achieved AUC of 0.9752 and AUPR of 0.9740 in cross-validation.

Outperformed several recent prediction models.

Validated effectiveness through case studies on three diseases.

Abstract

The emerging research shows that lncRNA has crucial research value in a series of complex human diseases. Therefore, the accurate identification of lncRNA-disease associations (LDAs) is very important for the warning and treatment of diseases. However, most of the existing methods have limitations in identifying nonlinear LDAs, and it remains a huge challenge to predict new LDAs. In this paper, a deep learning model based on a heterogeneous network and convolutional neural network (CNN) is proposed for lncRNA-disease association prediction, named HCNNLDA. The heterogeneous network containing the lncRNA, disease, and miRNA nodes, is constructed firstly. The embedding matrix of a lncRNA-disease node pair is constructed according to various biological premises about lncRNAs, diseases, and miRNAs. Then, the low-dimensional feature representation is fully learned by the convolutional neural network. In the end, the XGBoot classifier model is trained to predict the potential LDAs. HCNNLDA obtains a high AUC value of 0.9752 and AUPR of 0.9740 under the 5-fold cross-validation. The experimental results show that the proposed model has better performance than that of several latest prediction models. Meanwhile, the effectiveness of HCNNLDA in identifying novel LDAs is further demonstrated by case studies of three diseases. To sum up, HCNNLDA is a feasible calculation model to predict LDAs.