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Title: In-silico activity prediction, structure-based drug design, molecular docking and pharmacokinetic studies of selected quinazoline derivatives for their antiproliferative activity against triple negative breast cancer (MDA-MB231) cell line
Authors: Abdullahi, Sagiru Hamza
Participants: Uzairu, Adamu
Shallangwa, Gideon Adamu
Uba, Sani
Umar, Abdullahi Bello
Issue Date: 2022
Series/Report no.: Bulletin of the National Research Centre, Volume 46 (2022), Article number: 2
Abstract: In this research work Genetic function algorithm was employed to generate the QSAR models due to its ability to produce a vast population of model instead of just a single model. Four models were generated from the model building set and the first one was chosen because of its statistical significance.
URI: http://tailieuso.tlu.edu.vn/handle/DHTL/12599
Source: https://link.springer.com/article/10.1186/s42269-021-00690-z
ISSN: 2522-8307
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