Field of Research: Pharmacology
Name of author(s): Montañez-Godínez N., Martínez-Olguín A., Deeb O., Garduño-Juárez R., Ramírez-Galicia G.
Title of published work: "QSAR/QSPR as an application of Artificial Neural Networks"
Name of Journal or Book: "Artificial Neural Networks: Methods and Applications" as part of the "Methods in Molecular Biology" series. Prof. Hugh Cartwrigh (Ed)
Year: 2015
Pages: 319-333
Journal volume: Chapter 19
Publisher’s name and address: Springer publishers
Abstract:
Quantitative Structure–Activity Relationships (QSARs) and Quantitative Structure–Property Relationships (QSPRs) are mathematical models used to describe and predict a particular activity/property of compounds. On the other hand, the Artifi cial Neural Network (ANN) is a tool that emulates the human brain to solve very complex problems. The exponential need for new compounds in the drug industry requires alternatives for experimental methods to decrease development time and costs. This is where chemical computational methods have a great relevance, especially QSAR/QSPR-ANN. This chapter shows the importance of QSAR/QSPR-ANN and provides examples of its use.
Contact info of the contact author:
Name: Omar Deeb, PhD.
Address: Faculty of Pharmacy, Al-Quds University, Jerusalem,P.O Box: 51157, Palestine
E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
