摘要
拓扑的描述符(SATD ) 从与 23 氨基酸有关的 1262 个结构的变量的一个矩阵的原则部件分析导出的氨基酸的分数被采用在不同长度表示 125 肽的结构。量的 sequence-mobilitymodelings (QSMM ) 用部分最少的平方被构造(请) 并且支持向量机器(SVM ) 分别地。作为新氨基酸规模，包括与生物活性有关的丰富的信息的 SATD 容易被操作。更好的结果与获得与的那些相比被获得请，它显示 SVM 介绍了柔韧的稳定性和优秀预兆的能力 forelectrophoretic 活动性。这些结果证明在 QSMM 为应用 ofSATD 和 SVM 回归有宽前景。
Scores of amino acid topological descriptors （SATD） derived from principle components analysis of a matrix of 1262 structural variables related to 23 amino acids were employed to express the structure of 125 peptides in different length. Quantitative sequence-mobility modelings （QSMMs） were constructed using partial least square （PLS） and support vector machine （SVM）, respectively. As new amino acid scales, SATD including plentiful information related to biological activity were easily manipulated. Better results were obtained compared to those obtained with PLS, which indicated that SVM presented robust stability and excellent predictive ability for electrophoretic mobilities. These results show that there is a wide prospect for the applications of SATD and SVM regression in QSMMs.
