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Aixia Yan

Showing results (11-20 of 73) with videos related to

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Molecular Diversity|February 3, 2021
Classification models and SAR analysis on CysLT1 receptor antagonists using machine learning algorithmsHongzhao Wang, Zijian Qin, Aixia Yan
Molecular Informatics|March 1, 2017
Study of Structure-active Relationship for Inhibitors of HIV-1 Integrase LEDGF/p75 Interaction by Machine Learning MethodsYang Li, Yanbin Wu, Aixia Yan
Combinatorial Chemistry & High Throughput Screening|September 1, 2012
Classification of active and weakly active ST inhibitors of HIV-1 integrase using a support vector machineAixia Yan, Shouyi Xuan, Xiaoying Hu
International Journal of Molecular Sciences|March 28, 2009
Prediction of human intestinal absorption by GA feature selection and support vector machine regressionAixia Yan, Zhi Wang, Zongyuan Cai
Molecules (Basel, Switzerland)|October 14, 2023
Discovering the Active Ingredients of Medicine and Food Homologous Substances for Inhibiting the Cyclooxygenase-2 Metabolic Pathway by Machine Learning AlgorithmsYujia Tian, Zhixing Zhang, Aixia Yan
Bioorganic & Medicinal Chemistry Letters|May 15, 2017
QSAR studies of the bioactivity of hepatitis C virus (HCV) NS3/4A protease inhibitors by multiple linear regression (MLR) and support vector machine (SVM)Zijian Qin, Maolin Wang, Aixia Yan
Molecular Diversity|December 2, 2016
Computer modeling in predicting the bioactivity of human 5-lipoxygenase inhibitorsMengdi Zhang, Zhonghua Xia, Aixia Yan
Journal of Chemical Information and Modeling|December 5, 2017
Identification of Novel Aurora Kinase A (AURKA) Inhibitors via Hierarchical Ligand-Based Virtual ScreeningYue Kong, Andreas Bender, Aixia Yan
Drug Discovery Today|December 15, 2010
Aurora-A kinase inhibitor scaffolds and binding modesAixia Yan, Liyu Wang, Shuyu Xu, et al.
Molecular Informatics|July 29, 2016
Classification of Aurora-A Kinase Inhibitors Using Self-Organizing Map (SOM) and Support Vector Machine (SVM)Liyu Wang, Zhi Wang, Aixia Yan, et al.
Pageof 8

Showing results (11-20 of 73) with videos related to

Sort By:
Pageof 8
Molecular Diversity|February 3, 2021
Classification models and SAR analysis on CysLT1 receptor antagonists using machine learning algorithmsHongzhao Wang, Zijian Qin, Aixia Yan
Molecular Informatics|March 1, 2017
Study of Structure-active Relationship for Inhibitors of HIV-1 Integrase LEDGF/p75 Interaction by Machine Learning MethodsYang Li, Yanbin Wu, Aixia Yan
Combinatorial Chemistry & High Throughput Screening|September 1, 2012
Classification of active and weakly active ST inhibitors of HIV-1 integrase using a support vector machineAixia Yan, Shouyi Xuan, Xiaoying Hu
International Journal of Molecular Sciences|March 28, 2009
Prediction of human intestinal absorption by GA feature selection and support vector machine regressionAixia Yan, Zhi Wang, Zongyuan Cai
Molecules (Basel, Switzerland)|October 14, 2023
Discovering the Active Ingredients of Medicine and Food Homologous Substances for Inhibiting the Cyclooxygenase-2 Metabolic Pathway by Machine Learning AlgorithmsYujia Tian, Zhixing Zhang, Aixia Yan
Bioorganic & Medicinal Chemistry Letters|May 15, 2017
QSAR studies of the bioactivity of hepatitis C virus (HCV) NS3/4A protease inhibitors by multiple linear regression (MLR) and support vector machine (SVM)Zijian Qin, Maolin Wang, Aixia Yan
Molecular Diversity|December 2, 2016
Computer modeling in predicting the bioactivity of human 5-lipoxygenase inhibitorsMengdi Zhang, Zhonghua Xia, Aixia Yan
Journal of Chemical Information and Modeling|December 5, 2017
Identification of Novel Aurora Kinase A (AURKA) Inhibitors via Hierarchical Ligand-Based Virtual ScreeningYue Kong, Andreas Bender, Aixia Yan
Drug Discovery Today|December 15, 2010
Aurora-A kinase inhibitor scaffolds and binding modesAixia Yan, Liyu Wang, Shuyu Xu, et al.
Molecular Informatics|July 29, 2016
Classification of Aurora-A Kinase Inhibitors Using Self-Organizing Map (SOM) and Support Vector Machine (SVM)Liyu Wang, Zhi Wang, Aixia Yan, et al.
Pageof 8