Identification of Active Molecules against Thrombocytopenia through Machine Learning-Reference-Cited by-同舟云学术

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Identification of Active Molecules against Thrombocytopenia through Machine Learning

Published:2024-08-07 Issue:16 Volume:64 Page:6506-6520
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Yang Youyou¹,Gan Wenli¹,Lin Lei²,Wang Long¹,Wu Jianming³,Luo Jiesi³⁴^ORCID

Affiliation:

1. Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou 646000, China

2. School of Public Health, Southwest Medical University, Luzhou 646000, China

3. Basic Medical College, Southwest Medical University, Luzhou 646000, China

4. State Key Laboratory of Southwestern Chinese Medicine Resources, Chengdu University of Traditional Chinese Medicine, Chengdu 610075, China

Funder

National College Students Innovation and Entrepreneurship Training Program

Chengdu University of Traditional Chinese Medicine

Science and Technology Department of Sichuan Province

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.4c00718

Reference59 articles.

1. Linkage between the mechanisms of thrombocytopenia and thrombopoiesis

2. Thrombocytopenia in MDS: epidemiology, mechanisms, clinical consequences and novel therapeutic strategies

3. Chemotherapy induced thrombocytopenia in pediatric oncology

4. Prevention of transfusion-transmitted infections

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