Computer Science ›› 2015, Vol. 42 ›› Issue (2): 7-13.doi: 10.11896/j.issn.1002-137X.2015.02.002

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Research and Progress of microRNA Prediction Methods Based on Machine Learning

WANG Ying, LI Jin, WANG Lei, XU Cheng-zhen and CAI Zhong-xi   

  • Online:2018-11-14 Published:2018-11-14

Abstract: Traditional cloning experimental approaches are affected by the organizational and environmental impact,and the cost is high.The comparative method that belongs to the computational method is low sensitivity to the far evolutionary distance genes,and can’t predict the no homologous microRNAs.The machine learning method can resolve the restraints that comparative method dependents on the homologous gene.Firstly,this paper summarized the microRNA relevant biological knowledge which the machine learning is related to.Secondly,it outlined the general process and the latest research software and algorithms of machine learning based on microRNA prediction.Thirdly,starting from data selection,feature selection,classifier design,feature subset selection,class imbalance problem,performance evaluation and other aspects in terms of the essential elements of microRNA prediction based on the machine learning,it summarized the method and technology in each process,described their latest research progress.The approaches were contrasted and analyzed respectively in some process,and their respective advantages,disadvantages were summarized.Finally,summary and prospect of the research work on microRNA prediction based on machine learning were given.

Key words: microRNA,Machine learning,Classifier,Feature extraction,Class imbalance,Bioinformatics

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