2L-PCA: a two-level principal component analyzer for quantitative drug design and its applications.
2L-PCA: a two-level principal component analyzer for quantitative drug design and its applications.
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2L-PCA：定量药物设计的二级主成分分析仪及其应用
DOI：
10.18632/oncotarget.19757
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发表时间：
2017-09-19
期刊：
影响因子：
--
通讯作者：
Chou KC
中科院分区：
文献类型：
--
作者：
Du QS;Wang SQ;Xie NZ;Wang QY;Huang RB;Chou KC
基于主成分分析（PCA）方法，提出了一种两层主成分预测器（2L-PCA）。它可用于定量分析各种化合物和肽的功能或成为有用药物的潜力。一个层次是用于处理药物分子的物理化学性质，而另一个层次是用于处理其结构片段。该预测器具有自学习和反馈功能，可以自动提高预测精度。预计2L-PCA将成为一个非常有用的工具，在药物开发过程中及时提供各种有用的线索。
A two-level principal component predictor (2L-PCA) was proposed based on the principal component analysis (PCA) approach. It can be used to quantitatively analyze various compounds and peptides about their functions or potentials to become useful drugs. One level is for dealing with the physicochemical properties of drug molecules, while the other level is for dealing with their structural fragments. The predictor has the self-learning and feedback features to automatically improve its accuracy. It is anticipated that 2L-PCA will become a very useful tool for timely providing various useful clues during the process of drug development.