Literature DB >> 26342458

Recent developments in sample preparation and data pre-treatment in metabonomics research.

Ning Li1, Yi peng Song1, Huiru Tang2, Yulan Wang3.   

Abstract

Metabonomics is a powerful approach for biomarker discovery and an effective tool for pinpointing endpoint metabolic effects of external stimuli, such as pathogens and disease development. Due to its wide applications, metabonomics is required to deal with various biological samples of different properties. Hence sample preparation and corresponding data pre-treatment become important factors in ensuring validity of an investigation. In this review, we summarize some recent developments in metabonomics sample preparation and data-pretreatment procedures.
Copyright © 2015 Elsevier Inc. All rights reserved.

Keywords:  Data pre-treatment; Metabonomics research; Sample preparation

Mesh:

Year:  2015        PMID: 26342458     DOI: 10.1016/j.abb.2015.08.024

Source DB:  PubMed          Journal:  Arch Biochem Biophys        ISSN: 0003-9861            Impact factor:   4.013


  11 in total

1.  Metabolite quantification: A fluorescence-based method for urine sample normalization prior to 1H-NMR analysis.

Authors:  James Gerard Wolfsberger; Emily C Hunt; Sai Sumedha Bobba; Sharifa Love-Rutledge; Bernhard Vogler
Journal:  Metabolomics       Date:  2022-10-19       Impact factor: 4.747

2.  NMR Chemical Shift Ranges of Urine Metabolites in Various Organic Solvents.

Authors:  Benjamin Görling; Stefan Bräse; Burkhard Luy
Journal:  Metabolites       Date:  2016-09-02

Review 3.  Advances of Metabolomics in Fungal Pathogen-Plant Interactions.

Authors:  Fangfang Chen; Ruijing Ma; Xiao-Lin Chen
Journal:  Metabolites       Date:  2019-08-15

4.  Changes of Differential Urinary Metabolites after High-Intensive Training in Teenage Football Players.

Authors:  Ben Cao; Shuojia Liu; Lin Yang; Aiping Chi
Journal:  Biomed Res Int       Date:  2020-03-18       Impact factor: 3.411

Review 5.  Metabolomics: A Way Forward for Crop Improvement.

Authors:  Ali Razzaq; Bushra Sadia; Ali Raza; Muhammad Khalid Hameed; Fozia Saleem
Journal:  Metabolites       Date:  2019-12-14

6.  Comparison of HPLC and NMR for quantification of the main volatile fatty acids in rumen digesta.

Authors:  Mengyuan Wang; Haiying Wang; Huiru Zheng; Dusan Uhrin; Richard J Dewhurst; Rainer Roehe
Journal:  Sci Rep       Date:  2021-12-21       Impact factor: 4.379

7.  Siderophore biosynthesis coordinately modulated the virulence-associated interactive metabolome of uropathogenic Escherichia coli and human urine.

Authors:  Qiao Su; Tianbing Guan; Haitao Lv
Journal:  Sci Rep       Date:  2016-04-14       Impact factor: 4.379

8.  Non-targeted UHPLC-MS metabolomic data processing methods: a comparative investigation of normalisation, missing value imputation, transformation and scaling.

Authors:  Riccardo Di Guida; Jasper Engel; J William Allwood; Ralf J M Weber; Martin R Jones; Ulf Sommer; Mark R Viant; Warwick B Dunn
Journal:  Metabolomics       Date:  2016-04-15       Impact factor: 4.290

9.  Improving sample classification by harnessing the potential of 1H-NMR signal chemical shifts.

Authors:  Daniel Cañueto; Reza M Salek; Xavier Correig; Nicolau Cañellas
Journal:  Sci Rep       Date:  2018-08-08       Impact factor: 4.379

Review 10.  From Samples to Insights into Metabolism: Uncovering Biologically Relevant Information in LC-HRMS Metabolomics Data.

Authors:  Julijana Ivanisevic; Elizabeth J Want
Journal:  Metabolites       Date:  2019-12-17
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