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
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