Improved success of phenotype prediction of the human immunodeficiency virus type 1 from envelope variable loop 3 sequence using neural networks
Improved success of phenotype prediction of the human immunodeficiency virus type 1 from envelope variable loop 3 sequence using neural networks
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DOI：
10.1006/viro.2001.1087
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发表时间：
2001-09-15
期刊：
影响因子：
3.7
通讯作者：
Swanstrom, R
中科院分区：
文献类型：
--
作者：
Resch, W;Hoffman, N;Swanstrom, R
我们已经组装了两组HIV-1V3序列，它们具有明确的流行病学关系，与实验确定的辅助受体使用或MT-2细胞趋向性相关。这些数据集用于三个目的。首先，他们被用来测试现有的预测辅助受体使用和MT-2细胞趋向性的方法。在这些方法中，第11或25位碱性氨基酸的存在被证明是两种表型分类中最可靠的，尽管它对X4表型的预测能力不到50%。其次，我们使用序列集来训练神经网络，从V3基因型推断辅助受体的使用，比基于最好的基于基序的方法更成功，并且预测能力与基于最好的基于基序的方法的MT-2细胞趋向性相当。第三，我们使用序列集重新检查与不同表型相关的可变性模式，我们表明，使用训练好的神经网络预测的表型，可以从大的V3序列集复制与表型相关的序列模式。(C)2001年学术出版社。
We have assembled two sets of HIV-1 V3 sequences with defined epidemiologic relationships associated with experimentally determined coreceptor usage or MT-2 cell tropism. These data sets were used for three purposes. First, they were employed to test existing methods for predicting coreceptor usage and MT-2 cell tropism. Of these methods, the presence of one basic amino acid at position 11 or 25 proved to be most reliable for both phenotypic classifications, although its predictive power for the X4 phenotype was less then 50%. Second, we used the sequence sets to train neural networks to infer coreceptor usage from V3 genotype with better success than the best available motif-based method, and with a predictive power equal to that of the best motif-based method for MT-2 cell tropism. Third, we used the sequence sets to reexamine patterns of variability associated with the different phenotypes, and we showed that the phenotype-associated sequence patterns could be reproduced from large sets of V3 sequences using phenotypes predicted by the trained neural network. (C) 2001 Academic Press.