This article is a correction to:
Uncovering the pharmacology of Ginkgo biloba folium in the cell-type-specific targets of Parkinson’s disease
Yu-Chen Yan
Zhi-Heng Xu
Jian Wang
Wen-Bo Yu- Department of Neurology and National Research Center for Aging and Medicine & National Center for Neurological Disorders, State Key Laboratory of Medical Neurobiology, Huashan Hospital, Shanghai, China
A Corrigendum on
Uncovering the pharmacology of Ginkgo biloba folium in the cell-type-specific targets of Parkinson’s disease with a deep learning algorithm
by Yan Y-C, Xu Z-H, Wang J and Yu W-B (2022) Uncovering the pharmacology of Ginkgo biloba folium in the cell-type-specific targets of Parkinson’s disease. Front. Pharmacol. 13:1007556. doi: 10.3389/fphar.2022.1007556
In the published article, there was an error in the Funding statement. The Funding statement was not present in the original version. The correct Funding statement appears below.
“This work was financially supported by the National Natural Science Foundation of China (Award number(s): 81971194, 82171421, 91949118) and Science and Technology Commission of Shanghai Municipality (Award number(s): 2018SHZDZX01, 21S31902200); National Health Commission of the People’s Republic of China.”
The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Keywords: Parkinson’s disease, Ginkgo biloba folium, Network pharmacolgy, deep learning, Single-nuclei RNA sequencing
Citation: Yan Y-C, Xu Z-H, Wang J and Yu W-B (2023) Corrigendum: Uncovering the pharmacology of Ginkgo biloba folium in the cell-type-specific targets of Parkinson’s disease with a deep learning algorithm. Front. Pharmacol. 13:1115043. doi: 10.3389/fphar.2022.1115043
Received: 03 December 2022; Accepted: 13 December 2022;
Published: 12 January 2023.
Approved by:
Frontiers Editorial Office, Frontiers Media SA, SwitzerlandCopyright © 2023 Yan, Xu, Wang and Yu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Jian Wang, wangjian_hs@fudan.edu.cn; Wen-Bo Yu, yuwenbo@fudan.edu.cn