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A fuzzy based approach for prediction of biological activities of HIV -1 protease inhibitor compounds

机译:一种基于模糊的HIV -1蛋白酶抑制剂化合物的生物活性的方法

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A neuro-fuzzy based approach for predicting the HIV-1 inhibitor compounds activity has been designed when the molecular descriptor attributes of the compound are known. Standard Fuzzy ARTMAP (FAM) is provided with 196 data sets which is divided into 176 training data and 20 test data. The normalized data is given to the FAM network and the result indicates whether the compound is a suitable inhibitor or not. The result analysis is done with/ without GA for the dataset and GA-FAMR algorithm is used to optimize the relevance's assigned to the training data and the accuracy obtained is 93.09%.
机译:当化合物的分子描述符属性是已知的,已经设计了一种用于预测HIV-1抑制剂化合物活性的神经模糊方法。标准模糊ArtMap(FAM)提供了196个数据集,分为176个培训数据和20个测试数据。归一化数据给予FAM网络,结果表明该化合物是合适的抑制剂。结果分析使用/不具有GA的GA用于数据集,GA-FAMR算法用于优化分配给培训数据的相关性,所获得的准确性为93.09%。

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