Pharmacometabonomics: data processing and statistical analysis

Author:

Fu Jianbo1,Zhang Ying1,Liu Jin1,Lian Xichen1,Tang Jing2,Zhu Feng1

Affiliation:

1. College of Pharmaceutical Sciences in Zhejiang University, China

2. Department of Bioinformatics in Chongqing Medical University, China

Abstract

Abstract Individual variations in drug efficacy, side effects and adverse drug reactions are still challenging that cannot be ignored in drug research and development. The aim of pharmacometabonomics is to better understand the pharmacokinetic properties of drugs and monitor the drug effects on specific metabolic pathways. Here, we systematically reviewed the recent technological advances in pharmacometabonomics for better understanding the pathophysiological mechanisms of diseases as well as the metabolic effects of drugs on bodies. First, the advantages and disadvantages of all mainstream analytical techniques were compared. Second, many data processing strategies including filtering, missing value imputation, quality control-based correction, transformation, normalization together with the methods implemented in each step were discussed. Third, various feature selection and feature extraction algorithms commonly applied in pharmacometabonomics were described. Finally, the databases that facilitate current pharmacometabonomics were collected and discussed. All in all, this review provided guidance for researchers engaged in pharmacometabonomics and metabolomics, and it would promote the wide application of metabolomics in drug research and personalized medicine.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Zhejiang Province

National Key Research and Development Program of China

Fundamental Research Fund for Central Universities

Key Research and Development Program of Zhejiang Province

Information Technology Center, Zhejiang University

Publisher

Oxford University Press (OUP)

Subject

Molecular Biology,Information Systems

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