Transcriptionally Conditional Recurrent Neural Network for De Novo Drug Design-Reference-Cited by-同舟云学术

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Transcriptionally Conditional Recurrent Neural Network for De Novo Drug Design

Published:2024-07-25 Issue:15 Volume:64 Page:5844-5852
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Matsukiyo Yuki¹²^ORCID,Tengeiji Atsushi³,Li Chen²,Yamanishi Yoshihiro¹²^ORCID

Affiliation:

1. Department of Bioscience and Bioinformatics, Faculty of Computer Science and Systems Engineering, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka, Fukuoka 820-8502, Japan

2. Department of Complex Systems Science, Graduate School of Informatics, Nagoya University, Chikusa, Nagoya, Aichi 464-8601, Japan

3. Modality Research Laboratories I, Daiichi Sankyo Co., Ltd., 1-2-58 Hiromachi, Shinagawa, Tokyo 140-8710, Japan

Funder

Japan Society for the Promotion of Science

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.4c00531

Reference44 articles.

1. The art and practice of structure-based drug design: A molecular modeling perspective

2. Novel trends in high-throughput screening

3. DRUG-seq for miniaturized high-throughput transcriptome profiling in drug discovery

4. Adaptation of High-Throughput Screening in Drug Discovery—Toxicological Screening Tests

5. Design, synthesis and selection of DNA-encoded small-molecule libraries

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