TY - JOUR
T1 - Modern Deep Learning in Bioinformatics.
AU - Li, Haoyang
AU - Tian, Shuye
AU - Li, Yu
AU - Fang, Qiming
AU - Tan, Renbo
AU - Pan, Yijie
AU - Huang, Chao
AU - Xu, Ying
AU - Gao, Xin
N1 - KAUST Repository Item: Exported on 2020-10-01
PY - 2020/6/24
Y1 - 2020/6/24
N2 - Deep learning (DL) has shown explosive growth in its application to bioinformatics and has demonstrated thrillingly promising power to mine the complex relationship hidden in large-scale biological and biomedical data. A number of comprehensive reviews have been published on such applications, ranging from high-level reviews with future perspectives to those mainly serving as tutorials. These reviews have provided an excellent introduction to and guideline for applications of DL in bioinformatics, covering multiple types of machine learning (ML) problems, different DL architectures, and ranges of biological/biomedical problems. However, most of these reviews have focused on previous research, whereas current trends in the principled DL field and perspectives on their future developments and potential new applications to biology and biomedicine are still scarce. We will focus on modern DL, the ongoing trends and future directions of the principled DL field, and postulate new and major applications in bioinformatics.
AB - Deep learning (DL) has shown explosive growth in its application to bioinformatics and has demonstrated thrillingly promising power to mine the complex relationship hidden in large-scale biological and biomedical data. A number of comprehensive reviews have been published on such applications, ranging from high-level reviews with future perspectives to those mainly serving as tutorials. These reviews have provided an excellent introduction to and guideline for applications of DL in bioinformatics, covering multiple types of machine learning (ML) problems, different DL architectures, and ranges of biological/biomedical problems. However, most of these reviews have focused on previous research, whereas current trends in the principled DL field and perspectives on their future developments and potential new applications to biology and biomedicine are still scarce. We will focus on modern DL, the ongoing trends and future directions of the principled DL field, and postulate new and major applications in bioinformatics.
UR - http://hdl.handle.net/10754/663856
UR - https://academic.oup.com/jmcb/advance-article/doi/10.1093/jmcb/mjaa030/5861537
UR - http://www.scopus.com/inward/record.url?scp=85086934725&partnerID=8YFLogxK
U2 - 10.1093/jmcb/mjaa030
DO - 10.1093/jmcb/mjaa030
M3 - Article
C2 - 32573721
SN - 1674-2788
JO - Journal of Molecular Cell Biology
JF - Journal of Molecular Cell Biology
ER -