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Current Protein & Peptide Science

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ISSN (Print): 1389-2037
ISSN (Online): 1875-5550

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Research Article

ES-MDA: Enhanced Similarity-based MiRNA-Disease Association

Author(s): Li Xu * and Ge-Ning Jiang

Volume 21, Issue 11, 2020

Page: [1060 - 1067] Pages: 8

DOI: 10.2174/1389203721666200911151723

Price: $65

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Abstract

Accumulating evidence demonstrate that miRNAs can be treated as critical biomarkers in various complex human diseases. Thus, the identifications on potential miRNA-disease associations have become a hotpot for providing better understanding of disease pathology in this field. Recently, with various biological datasets, increasingly computational prediction approaches have been designed to uncover disease-related miRNAs for further experimental validation. To improve the prediction accuracy, several algorithms integrated miRNA similarities of known miRNA-disease associations to enhance the miRNA functional similarity network and disease similarities of known miRNA-disease associations to enhance the disease semantic similarity network. It is anticipated that machine learning methods would become an effective biological resource for clinical experimental guidance.

Keywords: microRNA, disease, lung cancer, network consistency projection, biological resources, pathology.

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