Open Access<strong>Predicting Proteasome Inhibition using Atomic Weighted Vector and Machine Learning</strong>
Author(s) -
Juan A. Castillo-Garit,
Yoan Martínez-López,
Efrain Chaluisa Quishpe,
Yailé Caballero,
Stephen J. Barigye,
Francisco Torrens
Publication year - 2018
Publication title -
proceedings of mol2net 2018, international conference on multidisciplinary sciences, 4th edition
Language(s) - English
Resource type - Conference proceedings
DOI - 10.3390/mol2net-04-05872
Subject(s) - quantitative structure–activity relationship , support vector machine , random forest , artificial intelligence , proteasome , decision tree , machine learning , perceptron , multilayer perceptron , ubiquitin , computer science , regression , chemistry , computational biology , artificial neural network , mathematics , biology , gene , biochemistry , statistics