计算机科学 ›› 2023, Vol. 50 ›› Issue (4): 369-387.doi: 10.11896/jsjkx.220500114

• 交叉&前沿 • 上一篇    下一篇

生物标志物智能识别关键技术:环状RNA与疾病关联预测研究综述

胡学钢1,2,3, 李扬1,2,3, 王磊4,5, 李培培1,2,3, 尤著宏6   

  1. 1 大数据知识工程教育部重点实验室(合肥工业大学) 合肥 230601
    2 合肥工业大学计算机与信息学院 合肥 230601
    3 合肥工业大学大知识科学研究院 合肥 230601
    4 枣庄学院信息科学与工程学院 山东 枣庄 277160
    5 广西科学院大数据与智能计算研究中心 南宁 530007
    6 西北工业大学计算机学院 西安 710129
  • 收稿日期:2022-05-13 修回日期:2022-09-19 出版日期:2023-04-15 发布日期:2023-04-06
  • 通讯作者: 王磊(leiwang@gxas.cn)
  • 作者简介:(jsjxhuxg@hfut.edu.cn)
  • 基金资助:
    国家重点研发计划(2016YFB1000901);国家自然科学基金(62172355,61806065,61702444);中央高校基本科研业务费专项资金(JZ2020HGQA0186)

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).

摘要: 生物标志物识别是实现“精准医疗”的一大基础,其对复杂疾病诊断、判断疾病分期及评价新药或新疗法在目标人群中的安全性和有效性具有重要作用。作为生物标志物智能识别关键技术,环状RNA与疾病关联预测是深入评测和衡量被试个体生物学过程、病理学过程及干预病理学反应的关键,是践行“精准医疗”的有效手段和途径之一。文中对基于生物大数据挖掘的环状RNA-疾病关联预测计算模型进行了全面梳理和展望。具体地,首先从环状RNA的研究背景、理化特性、功能等方面探讨了环状RNA与疾病之间的关系;然后调研了环状RNA和疾病公共数据库资源;接着从智能计算的角度梳理了环状RNA-疾病关联预测的4类计算方法,并分析了其优势与不足;最后讨论了环状RNA-疾病关联预测问题目前面临的挑战和未来可能的研究方向。

关键词: 精准医疗, 生物大数据, 环状RNA, 环状RNA-疾病关联, 计算模型

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

中图分类号: 

  • TP391
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