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

Author(s):

Li Xu * and Ge-Ning Jiang   Pages 1060 - 1067 ( 8 )

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.

Affiliation:

Department of Thoracic Surgery, Shanghai Pulmonary Hospital of Tongji University, Tongji University, Shanghai 201804, Department of Thoracic Surgery, Shanghai Pulmonary Hospital of Tongji University, Tongji University, Shanghai 201804

Graphical Abstract:

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