Publication Type : Journal Article
Publisher : Bentham Science
Source : Current Bioinformatics; Volume 20, Issue 2, Year 2025, e200524230118
Url : https://doi.org/10.2174/0115748936293219240426051148
Keywords : Diseases; machine learning methods; matrix completion methods; miRNA disease association; miRNAs; network approaches
Campus : Kochi
Year : 2025
Abstract : Recent evidence demonstrated the fundamental role of miRNAs as disease biomarkers and their role in disease progression and pathology. Identifying disease related miRNAs using computational approaches has become one of the trending topics in health informatics. Many biological databases and online tools were developed for uncovering novel disease-related miRNAs. Hence, a brief overview regarding the disease biomarkers, miRNAs as disease biomarkers and their role in complex disorders is given here. Various methods for calculating miRNA and disease similarities are included and the existing machine learning and network based computational approaches for detecting disease associated miRNAs are reviewed along with the benchmark dataset used. Finally, the performance matrices, validation measures and online tools used for miRNA Disease Association (MDA) predictions are also outlined.
Cite this Research Publication : S. Sujamol, E.R. Vimina, U. Krishnakumar. (2024). An Exploratory Review on Recent Computational Approaches Devised for MiRNA Disease Association Prediction, Current Bioinformatics; Volume 20, Issue 2, Year 2025, e200524230118. Publisher: Bentham Science (Q1, Impact Factor: 2.4).