Population-based De Novo Molecule Generation, Using Grammatical Evolution-Reference-Cited by-同舟云学术

Population-based De Novo Molecule Generation, Using Grammatical Evolution

Published:2018-11-05 Issue:11 Volume:47 Page:1431-1434
ISSN:0366-7022
Container-title:Chemistry Letters
language:en
Short-container-title:Chem. Lett.

Author:

Yoshikawa Naruki¹,Terayama Kei¹²³,Sumita Masato²,Homma Teruki⁴,Oono Kenta⁵,Tsuda Koji¹²⁶

Affiliation:

1. Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwa-no-ha, Kashiwa, Chiba 277-8561, Japan

2. RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihombashi, Chuo-ku, Tokyo 103-0027, Japan

3. Graduate School of Medicine, Kyoto University, Yoshida-Konoe-cho, Sakyo-ku, Kyoto 606-8501, Japan

4. RIKEN Systems and Structural Biology Center, Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan

5. Preferred Networks, Inc., 1-6-1 Otemachi, Chiyoda-ku, Tokyo 100-0004, Japan

6. National Institute for Materials Science, 1-2-1 Sengen, Tsukuba, Ibaraki 305-0047, Japan

Publisher

The Chemical Society of Japan

Subject

General Chemistry

Link

http://www.journal.csj.jp/doi/pdf/10.1246/cl.180665

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