Chou K C, Elrod D W
Computer-Aided Drug Discovery, Pharmacia & Upjohn, Kalamazoo, Michigan, 49007-4940, USA.
Biochem Biophys Res Commun. 1998 Nov 9;252(1):63-8. doi: 10.1006/bbrc.1998.9498.
The discriminant function algorithm was introduced to predict the subcellular location of proteins in prokaryotic organisms from their amino-acid composition. The rate of correct prediction for the three possible subcellular locations of prokaryotic proteins studied by Reinhardt and Hubbard (Nucleic Acid Research, 1998, 26:2230-2236) was 90% by the self-consistency test, and 87% by the jackknife test. These rates are considerably higher than the results recently reported by them using the neural network method. Furthermore, the test procedure adopted here is also more rigorous. The core of the current algorithm is the covariance matrix, through which the collective interactions among different amino-acid components of a protein can be reflected. It is anticipated that, owing to the intimate correlation of the function of a protein with its subcellular location, the current algorithm will become a useful tool for the systematic analysis of genome data.
引入判别函数算法，根据氨基酸组成预测原核生物中蛋白质的亚细胞定位。Reinhardt和Hubbard（《核酸研究》，1998年，26卷：2230 - 2236页）研究的原核生物蛋白质三种可能亚细胞定位的正确预测率，通过自一致性检验为90%，通过留一法检验为87%。这些比率显著高于他们最近使用神经网络方法报告的结果。此外，这里采用的测试程序也更严格。当前算法的核心是协方差矩阵，通过它可以反映蛋白质不同氨基酸组分之间的集体相互作用。由于蛋白质功能与其亚细胞定位密切相关，预计当前算法将成为系统分析基因组数据的有用工具。
