R包
计算机科学
瓶颈
管道(软件)
组分(热力学)
主成分分析
数据挖掘
计算生物学
人工智能
生物
计算科学
热力学
物理
嵌入式系统
程序设计语言
作者
Mengci Li,Shouli Wang,Guoxiang Xie,Xiaojing Ma,Tianlu Chen,Jia Wang
出处
期刊:Bioinformatics
[Oxford University Press]
日期:2017-12-23
卷期号:34 (10): 1792-1794
被引量:12
标识
DOI:10.1093/bioinformatics/btx834
摘要
Abstract Summary Pharmacokinetics (PK) is a long-standing bottleneck for botanical drug and traditional medicine research. By using an integrated phytochemical and metabolomics approach coupled with multivariate statistical analysis, we propose a new strategy, Poly-PK, to simultaneously monitor the performance of drug constituents and endogenous metabolites, taking into account both the diversity of the drug’s chemical composition and its complex effects on the mammalian metabolic pathways. Poly-PK is independent of specific measurement platforms and has been successfully applied in the PK studies of Puerh tea, a traditional Chinese medicine Huangqi decoction and many other multi-component drugs. Here, we introduce an R package, polyPK, the first and only automation of the data analysis pipeline of Poly-PK strategy. polyPK provides 10 functions for data pre-processing, differential compound identification and grouping, traditional PK parameters calculation, multivariate statistical analysis, correlations, cluster analyses and resulting visualization. It may serve a wide range of users, including pharmacologists, biologists and doctors, in understanding the metabolic fate of multi-component drugs. Availability and implementation polyPK package is freely available from the R archive CRAN (https://CRAN.R-project.org/package=polyPK). Supplementary information Supplementary data are available at Bioinformatics online.
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