一种新的预测醛糖还原酶抑制活性的神经网络集合启发式方法

Proceedings of the Fifth IEEE International Symposium on Signal Processing and Information Technology, 2005. Pub Date : 2005-12-21 DOI:10.1109/ISSPIT.2005.1577208

R. Parra-Hernandez, E. M. Laxdal, N. Dimopoulos, P. Alexiou

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引用次数: 5

摘要

在本文中，我们提出了一种机制，以获得一个基于神经网络的模型，预测一组化合物的酶抑制活性。该机制选择的化合物，在稀疏的一组，应该用来获得感兴趣的抑制活性的模型。也就是说，该机制旨在选择化合物的训练集，以确保基于神经网络的模型的训练将产生具有泛化能力的系统

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A new neural network ensemble heuristic for a predictor of the aldose reductase inhibitory activity

In this paper, we present a mechanism to obtain a neural network-based model that predicts an enzyme inhibitory activity of a group of compounds. The mechanism selects the compounds, among a sparse set of, that should be used to obtain models of the inhibitory activity of interest. That is, the mechanism is aimed to the selection of a training set of compounds which will ensure that the training of a neural network-based model will result in a system capable of generalization

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Proceedings of the Fifth IEEE International Symposium on Signal Processing and Information Technology, 2005.

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