An Improved Neural Network Ensemble Model of Aldose Reductase Inhibitory Activity

被引:0
|
作者
Hedayati, B. Keshavarz [1 ]
Parra-Hernandez, R. [1 ]
Laxdal, E. M. [1 ]
Dimopoulos, N. J. [1 ]
Alexiou, P. [2 ]
Demopoulos, V. J. [2 ]
机构
[1] Univ Victoria, Dept Elect & Comp Engn, Victoria, BC V8W 2Y2, Canada
[2] Aristotle Univ Thessaloniki, Dept Pharmaceut Chem, Thessaloniki, Greece
基金
加拿大自然科学与工程研究理事会;
关键词
DERIVATIVES;
D O I
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中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we improve the results based on a Neural Network-based model that predicts an enzyme (Aldose Reductase) inhibitory activity of a group of compounds. The improvement is due to the judicial selection of ensembles of trained Neural Networks to contribute to the final model. The method is validated on a family of compounds that is different from the families which were used in the training of the model. The results confirm an accurate, chemical-family-independent method that can predict Aldose Reductase inhibitory activity with excellent accuracy.
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页数:7
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