PBMDA: A novel and effective path-based computational model for miRNA-disease association prediction

• Published in: PLoS computational biology Vol. 13; no. 3; p. e1005455
• Main Authors: You, Zhu-Hong, Huang, Zhi-An, Zhu, Zexuan, Yan, Gui-Ying, Li, Zheng-Wei, Wen, Zhenkun, Chen, Xing
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 01.03.2017; Public Library of Science (PLoS)
• Subjects: Biological activity; Biological computing; Biology and life sciences; Biomarkers, Tumor - genetics; Case studies; Cell cycle; Colon; Colorectal cancer; Computer applications; Computer science; Computer Simulation; Disease; Diseases; Drugs; Esophageal cancer; Esophagus; Genetic Association Studies; Genetic Predisposition to Disease - epidemiology; Genetic Predisposition to Disease - genetics; Health aspects; Humans; Kidney cancer; Kidneys; Lupus; Medical prognosis; Medical research; Medicine and Health Sciences; Methods; MicroRNA; MicroRNAs; MicroRNAs - genetics; miRNA; Models, Genetic; Models, Statistical; Molecular modelling; Neoplasms; Neoplasms - epidemiology; Neoplasms - genetics; Pathogenesis; Physical Sciences; Prediction models; Predictions; Prevalence; Prognosis; Proteins; Research and Analysis Methods; Risk Assessment - methods; Risk Factors; RNA sequencing; Search algorithms; Signal Transduction - genetics; Similarity; Software; Software engineering; Thoracic surgery; Tumors; Urology

In the recent few years, an increasing number of studies have shown that microRNAs (miRNAs) play critical roles in many fundamental and important biological processes. As one of pathogenetic factors, the molecular mechanisms underlying human complex diseases still have not been completely understood...