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Molecular Diversity
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November 6, 2012
Using self-organizing map (SOM) and support vector machine (SVM) for classification of selectivity of ACAT inhibitors
Ling Wang, Maolin Wang, Aixia Yan, et al.
Chemical Research in Toxicology
|
April 5, 2023
Prediction and Structure-Activity Relationship Analysis on Ready Biodegradability of Chemical Using Machine Learning Method
Hongyan Yin, Cheng Lin, Yujia Tian, et al.
Drug Discovery Today
|
December 9, 2014
Targeting HIV-1 integrase with strand transfer inhibitors
Yang Li, Shouyi Xuan, Yue Feng, et al.
Chemical Biology & Drug Design
|
October 18, 2023
Ligand and structure based hierarchical virtual screening cascade for finding novel epidermal growth factor receptor inhibitors
Donghui Huo, Zhiqi Sun, Maolin Wang, et al.
Chemical Research in Toxicology
|
April 13, 2013
Carcinogenicity prediction of noncongeneric chemicals by a support vector machine
Min Zhong, Xianglei Nie, Aixia Yan, et al.
Chemical Biology & Drug Design
|
February 8, 2023
Prediction of bioactivities of microsomal prostaglandin E<sub>2</sub> synthase-1 inhibitors by machine learning algorithms
Yujia Tian, Zhenwu Yang, Hongzhao Wang, et al.
Molecular Diversity
|
November 3, 2012
Discriminating of ATP competitive Src kinase inhibitors and decoys using self-organizing map and support vector machine
Aixia Yan, Xiaoying Hu, Kai Wang, et al.
European Journal of Medicinal Chemistry
|
July 17, 2012
Classification of Aurora kinase inhibitors by self-organizing map (SOM) and support vector machine (SVM)
Aixia Yan, Xianglei Nie, Kai Wang, et al.
ACS Omega
|
March 31, 2025
Modeling and Interpretability Study of the Structure-Activity Relationship for Multigeneration EGFR Inhibitors
Zhiqi Sun, Donghui Huo, Jiangyu Guo, et al.
Combinatorial Chemistry & High Throughput Screening
|
May 5, 2016
Discrimination of Active and Weakly Active Human BACE1 Inhibitors Using Self-Organizing Map and Support Vector Machine
Hang Li, Maolin Wang, Ya-Nan Gong, et al.
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of 8
Search research articles
Search
Showing results (31-40 of 73) with videos related to
Sort By:
Page
of 8
Molecular Diversity
|
November 6, 2012
Using self-organizing map (SOM) and support vector machine (SVM) for classification of selectivity of ACAT inhibitors
Ling Wang, Maolin Wang, Aixia Yan, et al.
Chemical Research in Toxicology
|
April 5, 2023
Prediction and Structure-Activity Relationship Analysis on Ready Biodegradability of Chemical Using Machine Learning Method
Hongyan Yin, Cheng Lin, Yujia Tian, et al.
Drug Discovery Today
|
December 9, 2014
Targeting HIV-1 integrase with strand transfer inhibitors
Yang Li, Shouyi Xuan, Yue Feng, et al.
Chemical Biology & Drug Design
|
October 18, 2023
Ligand and structure based hierarchical virtual screening cascade for finding novel epidermal growth factor receptor inhibitors
Donghui Huo, Zhiqi Sun, Maolin Wang, et al.
Chemical Research in Toxicology
|
April 13, 2013
Carcinogenicity prediction of noncongeneric chemicals by a support vector machine
Min Zhong, Xianglei Nie, Aixia Yan, et al.
Chemical Biology & Drug Design
|
February 8, 2023
Prediction of bioactivities of microsomal prostaglandin E<sub>2</sub> synthase-1 inhibitors by machine learning algorithms
Yujia Tian, Zhenwu Yang, Hongzhao Wang, et al.
Molecular Diversity
|
November 3, 2012
Discriminating of ATP competitive Src kinase inhibitors and decoys using self-organizing map and support vector machine
Aixia Yan, Xiaoying Hu, Kai Wang, et al.
European Journal of Medicinal Chemistry
|
July 17, 2012
Classification of Aurora kinase inhibitors by self-organizing map (SOM) and support vector machine (SVM)
Aixia Yan, Xianglei Nie, Kai Wang, et al.
ACS Omega
|
March 31, 2025
Modeling and Interpretability Study of the Structure-Activity Relationship for Multigeneration EGFR Inhibitors
Zhiqi Sun, Donghui Huo, Jiangyu Guo, et al.
Combinatorial Chemistry & High Throughput Screening
|
May 5, 2016
Discrimination of Active and Weakly Active Human BACE1 Inhibitors Using Self-Organizing Map and Support Vector Machine
Hang Li, Maolin Wang, Ya-Nan Gong, et al.
Page
of 8