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Molecules (Basel, Switzerland)
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March 26, 2022
Identification of Pharmacophoric Fragments of DYRK1A Inhibitors Using Machine Learning Classification Models
Mengzhou Bi, Zhen Guan, Tengjiao Fan, et al.
Ecotoxicology and Environmental Safety
|
October 22, 2019
Prediction on the mutagenicity of nitroaromatic compounds using quantum chemistry descriptors based QSAR and machine learning derived classification methods
Yuxing Hao, Guohui Sun, Tengjiao Fan, et al.
Molecular Diversity
|
September 25, 2025
Discovery of potential RSV fusion protein inhibitors from benzimidazole derivatives using QSAR, molecular docking, and ADMET evaluation methods
Yini Xie, Runqing Jia, Tengjiao Fan, et al.
Molecular Diversity
|
June 27, 2025
Assessment of the rat acute oral toxicity of quinoline-based pharmaceutical scaffold molecules using QSTR, q-RASTR and machine learning methods
Jianing Xu, Ting Ren, Feifan Li, et al.
Biochemical Pharmacology
|
April 5, 2022
2-Deoxy-D-glucose increases the sensitivity of glioblastoma cells to BCNU through the regulation of glycolysis, ROS and ERS pathways: In vitro and in vivo validation
Xiaodong Sun, Tengjiao Fan, Guohui Sun, et al.
Journal of Hazardous Materials
|
June 14, 2020
In vivo toxicity of nitroaromatic compounds to rats: QSTR modelling and interspecies toxicity relationship with mouse
Yuxing Hao, Guohui Sun, Tengjiao Fan, et al.
Molecules (Basel, Switzerland)
|
November 9, 2018
In Silico Prediction of O⁶-Methylguanine-DNA Methyltransferase Inhibitory Potency of Base Analogs with QSAR and Machine Learning Methods
Guohui Sun, Tengjiao Fan, Xiaodong Sun, et al.
Pharmaceutics
|
August 26, 2023
QSAR and Chemical Read-Across Analysis of 370 Potential MGMT Inactivators to Identify the Structural Features Influencing Inactivation Potency
Guohui Sun, Peiying Bai, Tengjiao Fan, et al.
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of 3
Search research articles
Search
Showing results (21-30 of 28) with videos related to
Sort By:
Page
of 3
You have reached the last page of results.
This site can display upto 28 results.
Molecules (Basel, Switzerland)
|
March 26, 2022
Identification of Pharmacophoric Fragments of DYRK1A Inhibitors Using Machine Learning Classification Models
Mengzhou Bi, Zhen Guan, Tengjiao Fan, et al.
Ecotoxicology and Environmental Safety
|
October 22, 2019
Prediction on the mutagenicity of nitroaromatic compounds using quantum chemistry descriptors based QSAR and machine learning derived classification methods
Yuxing Hao, Guohui Sun, Tengjiao Fan, et al.
Molecular Diversity
|
September 25, 2025
Discovery of potential RSV fusion protein inhibitors from benzimidazole derivatives using QSAR, molecular docking, and ADMET evaluation methods
Yini Xie, Runqing Jia, Tengjiao Fan, et al.
Molecular Diversity
|
June 27, 2025
Assessment of the rat acute oral toxicity of quinoline-based pharmaceutical scaffold molecules using QSTR, q-RASTR and machine learning methods
Jianing Xu, Ting Ren, Feifan Li, et al.
Biochemical Pharmacology
|
April 5, 2022
2-Deoxy-D-glucose increases the sensitivity of glioblastoma cells to BCNU through the regulation of glycolysis, ROS and ERS pathways: In vitro and in vivo validation
Xiaodong Sun, Tengjiao Fan, Guohui Sun, et al.
Journal of Hazardous Materials
|
June 14, 2020
In vivo toxicity of nitroaromatic compounds to rats: QSTR modelling and interspecies toxicity relationship with mouse
Yuxing Hao, Guohui Sun, Tengjiao Fan, et al.
Molecules (Basel, Switzerland)
|
November 9, 2018
In Silico Prediction of O⁶-Methylguanine-DNA Methyltransferase Inhibitory Potency of Base Analogs with QSAR and Machine Learning Methods
Guohui Sun, Tengjiao Fan, Xiaodong Sun, et al.
Pharmaceutics
|
August 26, 2023
QSAR and Chemical Read-Across Analysis of 370 Potential MGMT Inactivators to Identify the Structural Features Influencing Inactivation Potency
Guohui Sun, Peiying Bai, Tengjiao Fan, et al.
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of 3