Results 51 to 60 of about 336,197 (187)

Quantitative Structure-Activity Relationship Studies for Potential Rho-Associated Protein Kinase Inhibitors

Journal of Chemistry, 2016
A series of pyridylthiazole derivatives developed by Lawrence et al. as Rho-associated protein kinase inhibitors were subjected to four-dimensional quantitative structure-activity relationship (4D-QSAR) analysis.
Giovanna Cardoso Gajo, Tamiris Maria de Assis, Letícia Cristina Assis, Teodorico Castro Ramalho, Elaine Fontes Ferreira da Cunha   +4 more
doaj   +1 more source

Synthesis, Biological Activity and Three-Dimensional Quantitative Structure-Activity Relationship (3D-QSAR) Study of Novel 4-Methyl-1,2,4-triazole-thioethers Containing gem-Dimethylcyclopropane Ring [PDF]

, 2020
Youpei Yu, Wengui Duan, Guishan Lin, Guo-Qiang Kang, Xiaoyu Wang, Fuhou Lei   +5 more
openalex   +1 more source

Deep learning for chemoinformatics

大数据, 2017
Deep learning have been successfully used in computer vision，speech recognition and natural language processing，leading to the rapid development of artificial intelligence.The key technology of deep learning was also applied to chemoinformatics，speeding ...
Youjun XU, Jianfeng PEI
doaj  

Synthesis, characterization, cytotoxic screening, and density functional theory studies of new derivatives of quinazolin-4(3H)-one Schiff bases

Research in Pharmaceutical Sciences, 2017
A series of novel derivatives of quinazolinone Schiff bases were synthesized from benzoic acid starting material and evaluated for potential cytotoxic activities against the human breast adenocarcinoma (MCF-7) and the human colon adenocarcinoma (HT-29 ...
Rezvan Rezaee Nasab, Farshid Hassanzadeh, Ghadam Ali Khodarahmi, Mahmoud Mirzaei, Mahboubeh Rostami, Ali Jahanian-Najaf abadi   +5 more
doaj   +1 more source

Additional file 3 of Quantitative Structure–Mutation–Activity Relationship Tests (QSMART) model for protein kinase inhibitor response prediction

, 2020
Liang‐Chin Huang, Wayland Yeung, Ye Wang, Huimin Cheng, Aarya Venkat, Sheng Li, Ping Ma, Khaled Rasheed, Natarajan Kannan   +8 more
openalex   +1 more source

Additional file 5 of Quantitative Structure–Mutation–Activity Relationship Tests (QSMART) model for protein kinase inhibitor response prediction

, 2020
Liang‐Chin Huang, Wayland Yeung, Ye Wang, Huimin Cheng, Aarya Venkat, Sheng Li, Ping Ma, Khaled Rasheed, Natarajan Kannan   +8 more
openalex   +1 more source

Validation of Quantitative Structure-Activity Relationship (QSAR) Model for Photosensitizer Activity Prediction [PDF]

, 2011
Neni Frimayanti, Mun Li Yam, Hong Boon Lee, Rozana Othman, Sharifuddin M. Zain, Noorsaadah Abd Rahman   +5 more
openalex   +1 more source

Predicting Flash Point of Organosilicon Compounds Using Quantitative Structure Activity Relationship Approach

Journal of Chemistry, 2014
The flash point (FP) of a compound is the primary property used in the assessment of fire hazards for flammable liquids and is amongst the crucial information that people handling flammable liquids must possess as far as industrial safety is concerned ...
Chen-Peng Chen, Chan-Cheng Chen, Hsu-Fang Chen   +2 more
doaj   +1 more source

Quantitative Structure-Activity Relationship Study of Fatty Acid Derivatives as Lubricant Additive

Jurnal Rekayasa Kimia & Lingkungan
Fatty acid compounds and their derivatives have been known in tribology as a source of bio-lubricant raw materials. New compounds were developed computationally to sort out the physical properties of the desired lubricant additive before synthesis in the
Rahmawita Sugesti, Komar Sutriah, Mohammad Khotib   +2 more
doaj   +1 more source

Additional file 4 of Quantitative Structure–Mutation–Activity Relationship Tests (QSMART) model for protein kinase inhibitor response prediction

, 2020
Liang‐Chin Huang, Wayland Yeung, Ye Wang, Huimin Cheng, Aarya Venkat, Sheng Li, Ping Ma, Khaled Rasheed, Natarajan Kannan   +8 more
openalex   +1 more source