Improved GNNs for Log <i>D</i><sub>7.4</sub> Prediction by Transferring Knowledge from Low-Fidelity Data-Reference-Cited by-同舟云学术

Improved GNNs for Log D_7.4 Prediction by Transferring Knowledge from Low-Fidelity Data

Published:2023-03-31 Issue:8 Volume:63 Page:2345-2359
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Duan Yan-Jing¹^ORCID,Fu Li¹,Zhang Xiao-Chen²,Long Teng-Zhi¹^ORCID,He Yuan-Hang¹,Liu Zhao-Qian¹^ORCID,Lu Ai-Ping³,Deng Ya-Feng⁴,Hsieh Chang-Yu⁵^ORCID,Hou Ting-Jun⁵^ORCID,Cao Dong-Sheng¹³^ORCID

Affiliation:

1. Xiangya School of Pharmaceutical Sciences, Central South University, Changsha 410013, Hunan, P. R. China

2. School of Information Technology, Shangqiu Normal University, Shangqiu 476000, Henan, P. R. China

3. Institute for Advancing Translational Medicine in Bone & Joint Diseases, School of Chinese Medicine, Hong Kong Baptist University, Hong Kong SAR 999077, P. R. China

4. CarbonSilicon AI Technology Co., Ltd., Hangzhou 310018, Zhejiang, P. R. China

5. Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, Zhejiang, P. R. China

Funder

Science and Technology Bureau, Changsha

Ministry of Science and Technology of the People's Republic of China

Natural Science Foundation of?Hunan Province

Science and Technology Program of Hunan Province

Natural Science Foundation for Distinguished Young Scholars of Hunan Province

National Natural Science Foundation of China

Guangdong Province for Science and Technology Innovative Young Talents

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry