Review of the Applications of Deep Learning in Bioinformatics

被引:45
|
作者
Zhang, Yongqing [1 ,2 ]
Yan, Jianrong [3 ]
Chen, Siyu [2 ]
Gong, Meiqin [4 ]
Gao, Dongrui [2 ]
Zhu, Min [3 ]
Gan, Wei [3 ]
机构
[1] Univ Elect Sci & Technol China, Sch Comp Sci & Engn, Chengdu 610054, Peoples R China
[2] Chengdu Univ Informat Technol, Sch Comp Sci, Chengdu 610225, Peoples R China
[3] Sichuan Univ, Sch Comp Sci, Chengdu 610065, Peoples R China
[4] Sichuan Univ, West China Univ Hosp 2, Chengdu 610041, Peoples R China
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
Bioinformatics; biomedical; deep learning; biological data; high-throughput; high-dimensional; CONVOLUTIONAL NEURAL-NETWORKS; LIGAND-BINDING AFFINITIES; BRAIN-TUMOR SEGMENTATION; DRUG DISCOVERY; PREDICTION; CLASSIFICATION; PROTEINS; SPECIFICITIES; ARCHITECTURES; FRAMEWORK;
D O I
10.2174/1574893615999200711165743
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Rapid advances in biological research over recent years have significantly enriched biological and medical data resources. Deep learning-based techniques have been successfully utilized to process data in this field, and they have exhibited state-of-the-art performances even on high-dimensional, nonstructural, and black-box biological data. The aim of the current study is to provide an overview of the deep learning-based techniques used in biology and medicine and their state-of-the-art applications. In particular, we introduce the fundamentals of deep learning and then review the success of applying such methods to bioinformatics, biomedical imaging, biomedicine, and drug discovery. We also discuss the challenges and limitations of this field, and outline possible directions for further research.
引用
收藏
页码:898 / 911
页数:14
相关论文
共 50 条
  • [31] Deep Learning Applications in Solid Waste Management: A Deep Literature Review
    Shahab, Sana
    Anjum, Mohd
    Umar, M. Sarosh
    [J]. INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2022, 13 (03) : 381 - 395
  • [32] A Review on Bayesian Deep Learning in Healthcare: Applications and Challenges
    Abdullah, Abdullah A.
    Hassan, Masoud M.
    Mustafa, Yaseen T.
    [J]. IEEE ACCESS, 2022, 10 : 36538 - 36562
  • [33] A review of hybrid deep learning applications for streamflow forecasting
    Ng, K. W.
    Huang, Y. F.
    Koo, C. H.
    Chong, K. L.
    El-Shafie, Ahmed
    Ahmed, Ali Najah
    [J]. JOURNAL OF HYDROLOGY, 2023, 625
  • [34] Applications of deep learning in detection of glaucoma: A systematic review
    Mirzania, Delaram
    Thompson, Atalie C.
    Muir, Kelly W.
    [J]. EUROPEAN JOURNAL OF OPHTHALMOLOGY, 2021, 31 (04) : 1618 - 1642
  • [35] A review on quantum computing and deep learning algorithms and their applications
    Valdez, Fevrier
    Melin, Patricia
    [J]. SOFT COMPUTING, 2023, 27 (18) : 13217 - 13236
  • [36] Applications of deep learning in precision weed management: A review
    Rai, Nitin
    Zhang, Yu
    Ram, Billy G.
    Schumacher, Leon
    Yellavajjala, Ravi K.
    Bajwa, Sreekala
    Sun, Xin
    [J]. COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2023, 206
  • [37] A Review on Deep Learning Applications in Prognostics and Health Management
    Zhang, Liangwei
    Lin, Jing
    Liu, Bin
    Zhang, Zhicong
    Yan, Xiaohui
    Wei, Muheng
    [J]. IEEE ACCESS, 2019, 7 : 162415 - 162438
  • [38] Applications of deep learning in physical oceanography: a comprehensive review
    Zhao, Qianlong
    Peng, Shiqiu
    Wang, Jingzhen
    Li, Shaotian
    Hou, Zhengyu
    Zhong, Guoqiang
    [J]. FRONTIERS IN MARINE SCIENCE, 2024, 11
  • [39] A review on quantum computing and deep learning algorithms and their applications
    Fevrier Valdez
    Patricia Melin
    [J]. Soft Computing, 2023, 27 : 13217 - 13236
  • [40] Deep Learning in Construction: Review of Applications and Potential Avenues
    Jacobsen, Emil L.
    Teizer, Jochen
    [J]. JOURNAL OF COMPUTING IN CIVIL ENGINEERING, 2022, 36 (02)