Identification of miRNA–disease associations via deep forest ensemble learning based on autoencoder

• Published in: Briefings in bioinformatics Vol. 23; no. 3
• Main Authors: Liu, Wei, Lin, Hui, Huang, Li, Peng, Li, Tang, Ting, Zhao, Qi, Yang, Li
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 13.05.2022; Oxford Publishing Limited (England)
• Subjects: Breast; Case studies; Colon; Computer applications; Disease; Ensemble learning; Feature extraction; Lung cancer; Lung diseases; MicroRNAs; miRNA; Predictions; Representations; Ribonucleic acid; RNA; Software; Tumors; deep forest ensemble learning; miRNA–disease association prediction; deep autoencoder; feature representation

Abstract Increasing evidences show that the occurrence of human complex diseases is closely related to microRNA (miRNA) variation and imbalance. For this reason, predicting disease-related miRNAs is essential for the diagnosis and treatment of complex human diseases. Although some current computatio...