Ge-Ning Jiang and Li Xu * Pages 1 - 9 ( 9 )
Accumulating evidences 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.
microRNA, disease, lung cancer, network consistency projection
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