A Review of Deep Learning in Computer-Aided Drug Design

Chih Hung Chang; Che Lun Hung; Chuan Yi Tang

doi:10.1109/BIBM47256.2019.8982968

A Review of Deep Learning in Computer-Aided Drug Design

Chih Hung Chang
, Che Lun Hung
, Chuan Yi Tang

Department of Computer Science and Information Engineering

Providence University Taiwan

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

7 Scopus citations

Abstract

Recently, Deep Learning has been applied to many medical domains, such as medical image analysis, bioinformatic, biochemistry, drug design, and so forth, to improve the performance that is superior to traditional computational approaches; especially in computer-aided drug design. Many AI-driven drug discovery startups have utilized deep learning methodology to achieve the significant improvement of searching candidate compounds, predicting functions, and so forth. Therefore, using AI to facilitate drug design is the trend in the coming future. In this study, a comprehensive review of the current state-of-the-art in Computer-Aided Drug Design using deep learning methods is presented. Meanwhile, the challenges and potential of these methods are also highlighted.

Original language	English
Title of host publication	Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019
Editors	Illhoi Yoo, Jinbo Bi, Xiaohua Tony Hu
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1856-1861
Number of pages	6
ISBN (Electronic)	9781728118673
DOIs	https://doi.org/10.1109/BIBM47256.2019.8982968
State	Published - 11 2019
Event	2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019 - San Diego, United States Duration: 18 11 2019 → 21 11 2019

Publication series

Name	Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019

Conference

Conference	2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019
Country/Territory	United States
City	San Diego
Period	18/11/19 → 21/11/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Keywords

Artificial Intelligence
Compound Searching
Computer-Aided Drug Design
Deep Learning

Access to Document

10.1109/BIBM47256.2019.8982968

Cite this

Chang, C. H., Hung, C. L., & Tang, C. Y. (2019). A Review of Deep Learning in Computer-Aided Drug Design. In I. Yoo, J. Bi, & X. T. Hu (Eds.), Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019 (pp. 1856-1861). Article 8982968 (Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIBM47256.2019.8982968

Chang, Chih Hung ; Hung, Che Lun ; Tang, Chuan Yi. / A Review of Deep Learning in Computer-Aided Drug Design. Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019. editor / Illhoi Yoo ; Jinbo Bi ; Xiaohua Tony Hu. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 1856-1861 (Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019).

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title = "A Review of Deep Learning in Computer-Aided Drug Design",

abstract = "Recently, Deep Learning has been applied to many medical domains, such as medical image analysis, bioinformatic, biochemistry, drug design, and so forth, to improve the performance that is superior to traditional computational approaches; especially in computer-aided drug design. Many AI-driven drug discovery startups have utilized deep learning methodology to achieve the significant improvement of searching candidate compounds, predicting functions, and so forth. Therefore, using AI to facilitate drug design is the trend in the coming future. In this study, a comprehensive review of the current state-of-the-art in Computer-Aided Drug Design using deep learning methods is presented. Meanwhile, the challenges and potential of these methods are also highlighted.",

keywords = "Artificial Intelligence, Compound Searching, Computer-Aided Drug Design, Deep Learning",

author = "Chang, \{Chih Hung\} and Hung, \{Che Lun\} and Tang, \{Chuan Yi\}",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019 ; Conference date: 18-11-2019 Through 21-11-2019",

year = "2019",

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series = "Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Chang, CH, Hung, CL & Tang, CY 2019, A Review of Deep Learning in Computer-Aided Drug Design. in I Yoo, J Bi & XT Hu (eds), Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019., 8982968, Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019, Institute of Electrical and Electronics Engineers Inc., pp. 1856-1861, 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019, San Diego, United States, 18/11/19. https://doi.org/10.1109/BIBM47256.2019.8982968

A Review of Deep Learning in Computer-Aided Drug Design. / Chang, Chih Hung; Hung, Che Lun; Tang, Chuan Yi.
Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019. ed. / Illhoi Yoo; Jinbo Bi; Xiaohua Tony Hu. Institute of Electrical and Electronics Engineers Inc., 2019. p. 1856-1861 8982968 (Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - Recently, Deep Learning has been applied to many medical domains, such as medical image analysis, bioinformatic, biochemistry, drug design, and so forth, to improve the performance that is superior to traditional computational approaches; especially in computer-aided drug design. Many AI-driven drug discovery startups have utilized deep learning methodology to achieve the significant improvement of searching candidate compounds, predicting functions, and so forth. Therefore, using AI to facilitate drug design is the trend in the coming future. In this study, a comprehensive review of the current state-of-the-art in Computer-Aided Drug Design using deep learning methods is presented. Meanwhile, the challenges and potential of these methods are also highlighted.

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KW - Compound Searching

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Chang CH, Hung CL, Tang CY. A Review of Deep Learning in Computer-Aided Drug Design. In Yoo I, Bi J, Hu XT, editors, Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 1856-1861. 8982968. (Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019). doi: 10.1109/BIBM47256.2019.8982968

A Review of Deep Learning in Computer-Aided Drug Design

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