Bayesian machine learning to discover Bruton’s tyrosine kinase inhibitors-Reference-Cited by-同舟云学术

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Bayesian machine learning to discover Bruton’s tyrosine kinase inhibitors

Published:2020-08-18 Issue:4 Volume:96 Page:1114-1122
ISSN:1747-0277
Container-title:Chemical Biology & Drug Design
language:en
Short-container-title:Chem Biol Drug Des

Author:

Wang Jian¹²^ORCID,Ran Ting³,Chen Yadong¹,Lu Tao¹

Affiliation:

1. State Key Laboratory of Natural Medicines China Pharmaceutical University Nanjing China

2. Zhejiang Pharmaceutical College Ningbo China

3. Fujian Provincial Key Laboratory of Innovative Drug Target Research School of Pharmaceutical Sciences Xiamen University Xiamen China

Publisher

Wiley

Subject

Molecular Medicine,Biochemistry,Drug Discovery,Pharmacology,Organic Chemistry

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/cbdd.13656

Reference46 articles.

1. Ibrutinib and novel BTK inhibitors in clinical development

2. Cross-Validation Methods

3. Mutations in Btk in Patients with Presumed X-Linked Agammaglobulinemia

4. Specific Btk inhibition suppresses B cell– and myeloid cell–mediated arthritis

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Machine learning-based classification models for non-covalent Bruton’s tyrosine kinase inhibitors: predictive ability and interpretability;Molecular Diversity;2023-07-21

2. Machine Learning-Based Classification Models for Non-Covalent Bruton's Tyrosine Kinase Inhibitors: Predictive Ability and Interpretability;2023-05-11

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