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Aixia Yan

Showing results (51-60 of 73) with videos related to

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Molecular Informatics|August 6, 2016
Using Support Vector Machine (SVM) for Classification of Selectivity of H1N1 Neuraminidase InhibitorsYang Li, Yue Kong, Mengdi Zhang, et al.
Current Computer-Aided Drug Design|September 21, 2019
Quantitative Structure-Activity Relationship Study for HIV-1 LEDGF/p75 InhibitorsYang Li, Yujia Tian, Yao Xi, et al.
Bioorganic & Medicinal Chemistry Letters|March 23, 2011
Prediction of biological activity of Aurora-A kinase inhibitors by multilinear regression analysis and support vector machineAixia Yan, Yang Chong, Liyu Wang, et al.
Combinatorial Chemistry & High Throughput Screening|April 15, 2016
Self-Organizing Map (SOM) and Support Vector Machine (SVM) Models for the Prediction of Human Epidermal Growth Factor Receptor (EGFR/ ErbB-1) InhibitorsYue Kong, Dan Qu, Xiaoyan Chen, et al.
Molecular Diversity|May 4, 2023
Classification of FLT3 inhibitors and SAR analysis by machine learning methodsYunyang Zhao, Yujia Tian, Xiaoyang Pang, et al.
Chemical Biology & Drug Design|December 25, 2018
SAR study on inhibitors of GIIA secreted phospholipase A<sub>2</sub> using machine learning methodsShengde Zhang, Yang Li, Zijian Qin, et al.
Molecular Diversity|July 21, 2023
Machine learning-based classification models for non-covalent Bruton's tyrosine kinase inhibitors: predictive ability and interpretabilityGuo Li, Jiaxuan Li, Yujia Tian, et al.
Molecular Diversity|June 23, 2022
Classification models and SAR analysis on HDAC1 inhibitors using machine learning methodsRourou Li, Yujia Tian, Zhenwu Yang, et al.
Combinatorial Chemistry & High Throughput Screening|October 25, 2013
Classification of Aurora B kinase inhibitors using computational modelsRuizi Liu, Xianglei Nie, Min Zhong, et al.
Molecular Informatics|August 2, 2016
Probability Based hERG Blocker ClassifiersZhi Wang, Hamse Y Mussa, Robert Lowe, et al.
Pageof 8

Showing results (51-60 of 73) with videos related to

Sort By:
Pageof 8
Molecular Informatics|August 6, 2016
Using Support Vector Machine (SVM) for Classification of Selectivity of H1N1 Neuraminidase InhibitorsYang Li, Yue Kong, Mengdi Zhang, et al.
Current Computer-Aided Drug Design|September 21, 2019
Quantitative Structure-Activity Relationship Study for HIV-1 LEDGF/p75 InhibitorsYang Li, Yujia Tian, Yao Xi, et al.
Bioorganic & Medicinal Chemistry Letters|March 23, 2011
Prediction of biological activity of Aurora-A kinase inhibitors by multilinear regression analysis and support vector machineAixia Yan, Yang Chong, Liyu Wang, et al.
Combinatorial Chemistry & High Throughput Screening|April 15, 2016
Self-Organizing Map (SOM) and Support Vector Machine (SVM) Models for the Prediction of Human Epidermal Growth Factor Receptor (EGFR/ ErbB-1) InhibitorsYue Kong, Dan Qu, Xiaoyan Chen, et al.
Molecular Diversity|May 4, 2023
Classification of FLT3 inhibitors and SAR analysis by machine learning methodsYunyang Zhao, Yujia Tian, Xiaoyang Pang, et al.
Chemical Biology & Drug Design|December 25, 2018
SAR study on inhibitors of GIIA secreted phospholipase A<sub>2</sub> using machine learning methodsShengde Zhang, Yang Li, Zijian Qin, et al.
Molecular Diversity|July 21, 2023
Machine learning-based classification models for non-covalent Bruton's tyrosine kinase inhibitors: predictive ability and interpretabilityGuo Li, Jiaxuan Li, Yujia Tian, et al.
Molecular Diversity|June 23, 2022
Classification models and SAR analysis on HDAC1 inhibitors using machine learning methodsRourou Li, Yujia Tian, Zhenwu Yang, et al.
Combinatorial Chemistry & High Throughput Screening|October 25, 2013
Classification of Aurora B kinase inhibitors using computational modelsRuizi Liu, Xianglei Nie, Min Zhong, et al.
Molecular Informatics|August 2, 2016
Probability Based hERG Blocker ClassifiersZhi Wang, Hamse Y Mussa, Robert Lowe, et al.
Pageof 8