Pillai Satish, Good Benjamin, Richman Douglas, Corbeil Jacques
University of California, San Diego, La Jolla, California 92093, USA.
AIDS Res Hum Retroviruses. 2003 Feb;19(2):145-9. doi: 10.1089/088922203762688658.
The particular coreceptor used by a strain of HIV-1 to enter a host cell is highly indicative of its pathology. HIV-1 coreceptor usage is primarily determined by the amino add sequences of the V3 loop region of the viral envelope glycoprotein. The canonical approach to sequence-based prediction of coreceptor usage was derived via statistical analysis of a less reliable and significantly smaller data set than is presently available. We aimed to produce a superior phenotypic classifier by applying modern machine learning (ML) techniques to the current database of V3 loop sequences with known phenotype. The trained classifiers along with the sequence data are available for public use at the supplementary website: http://genomiac2.ucsd.edu:8080/wetcat/v3.html and http://www.cs.waikato.ac.nz/ml/weka[corrected].
HIV-1毒株进入宿主细胞所使用的特定共受体对其病理特征具有高度指示性。HIV-1共受体的使用主要由病毒包膜糖蛋白V3环区域的氨基酸序列决定。基于序列预测共受体使用情况的传统方法是通过对一个比目前可用数据集可靠性更低且规模小得多的数据集进行统计分析得出的。我们旨在通过将现代机器学习（ML）技术应用于具有已知表型的V3环序列当前数据库，来生成一个更优的表型分类器。经过训练的分类器以及序列数据可在以下补充网站供公众使用：http://genomiac2.ucsd.edu:8080/wetcat/v3.html和http://www.cs.waikato.ac.nz/ml/weka[已修正] 。
