Computer Science ›› 2023, Vol. 50 ›› Issue (4): 369-387.doi: 10.11896/jsjkx.220500114

• Interdiscipline & Frontier • Previous Articles     Next Articles

Key Technologies of Intelligent Identification of Biomarkers:Review of Research on Association Prediction Between Circular RNA and Disease

HU Xuegang1,2,3, LI Yang1,2,3, WANG Lei4,5, LI Peipei1,2,3, YOU Zhuhong6   

  1. 1 Key Laboratory of Knowledge Engineering with Big Data(Hefei University of Technology),Ministry of Education,Hefei 230601,China
    2 School of Computer Science and Information Engineering,Hefei University of Technology,Hefei 230601,China
    3 Research Institute of Big Knowledge,Hefei University of Technology,Hefei 230601,China
    4 College of Information Science and Engineering,Zaozhuang University,Zaozhuang,Shandong 277160,China
    5 Big Data and Intelligent Computing Research Center,Guangxi Academy of Sciences,Nanning 530007,China
    6 School of Computer Science,Northwestern Polytechnical University,Xi’an 710129,China
  • Received:2022-05-13 Revised:2022-09-19 Online:2023-04-15 Published:2023-04-06
  • About author:HU Xuegang,born in 1961,Ph.D,professor,Ph.D supervisor.His main research interests include data mining and knowledge engineering.
    WANG Lei,born in 1982,Ph.D,professor,Ph.D supervisor.His main research interests include big data analysis,data mining and its applications in bioinformatics.
  • Supported by:
    National Key Research and Development Program of China(2016YFB1000901),National Natural Science Foundation of China(62172355,61806065,61702444) and Fundamental Research Funds for the Central Universities(JZ2020HGQA0186).

Abstract: Biomarker recognition is a major basis for achieving precision medicine,which plays an important role in diagnosing complex diseases,judging disease stages and evaluating the safety and effectiveness of new drugs or therapies in the target population.As the key technology of intelligent identification of biomarkers,the prediction of the association between circular RNA and disease is the key to deeply evaluate and measure the biological process,pathological process and intervention pathological response of subjects,and is one of the effective means and approaches to practice “precision medicine”.This paper comprehensively combs and prospects the circular RNA disease association prediction model in biological big data.Specifically,it first discusses the relationship between circRNA and disease in terms of the research background,physicochemical properties and functions of circ-RNAs.Then,it investigates the public database resources of circRNAs and diseases,and summarizes four computational methods of circRNA-disease association prediction from the perspective of computational models,and analyzes their advantages and shortcomings.Finally,this paper discusses the current challenges and future possible research directions of circRNA-disease association prediction problem.

Key words: Precision medicine, Biological big data, CircRNA, CircRNA-disease association, Computational model

CLC Number: 

  • TP391
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