Publicación:
QSAR/QSPR as an Application of Artificial Neural Networks

Unidades académicas

Unidad Académica
Instituto de Química Aplicada
Este instituto atiende a las necesidades de aplicación del conocimiento tanto en el área química como en los temas multidisciplinarios

Grado Académico

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Resumen

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 Artificial 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.

Descripción

Citación

Montañez-Godínez, N., Martínez-Olguín, A. C., Deeb, O., Garduño-Juárez, R., & Ramírez-Galicia, G. (2015). QSAR/QSPR as an application of artificial neural networks. En Artificial Neural Networks (pp. 319–333). Springer New York, NY. https://doi.org/10.1007/978-1-4939-2239-0_19

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