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Development of analytical workflows and bioinformatic programs for mass spectrometry-based metabolomics Yu, Huaxu
Abstract
Quantitative determination of metabolite concentrations in biological samples is fundamental to biological and clinical research. Metabolomics analyzes the entire set of metabolites in a given biological system. It is an emerging technology in the post-genomic era to interrogate cellular biochemistry, perform diagnostic testing, stratify patient populations, and characterize biochemical mechanisms of disease. Recent successes in metabolomics demonstrate the central role of mass spectrometry (MS) in small molecule quantification, owing to its high sensitivity, high throughput, and broad metabolic coverage. Even though diverse MS instruments have been developed for metabolite quantification, it is still challenging to quantify the entire metabolome accurately and precisely. Besides MS hardware advances, quantitative metabolomics also requires extensive efforts in other analytical and bioinformatic methodology development. For a given MS platform, analytical method development focuses on laboratory practice, including sample handling, metabolome extraction, and data acquisition. In comparison, bioinformatic method development emphasizes computational data processing, such as data calibration, data curation, and statistical analysis. The subsequent chapters detail the development of analytical and bioinformatic solutions for quantitative metabolomics from improving metabolic coverage, analytical accuracy, analytical precision, and statistical analysis. Lastly, this thesis describes a metabolomics study of mouse brain regional differences in metabolism between males and females. Collectively my studies of quantitative metabolomics improve quantitative performance, deepen our knowledge of the MS-based quantification process, and facilitate the generation of confident biological conclusions.
Item Metadata
| Title |
Development of analytical workflows and bioinformatic programs for mass spectrometry-based metabolomics
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| Creator | |
| Supervisor | |
| Publisher |
University of British Columbia
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| Date Issued |
2023
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| Description |
Quantitative determination of metabolite concentrations in biological samples is fundamental to biological and clinical research. Metabolomics analyzes the entire set of metabolites in a given biological system. It is an emerging technology in the post-genomic era to interrogate cellular biochemistry, perform diagnostic testing, stratify patient populations, and characterize biochemical mechanisms of disease. Recent successes in metabolomics demonstrate the central role of mass spectrometry (MS) in small molecule quantification, owing to its high sensitivity, high throughput, and broad metabolic coverage. Even though diverse MS instruments have been developed for metabolite quantification, it is still challenging to quantify the entire metabolome accurately and precisely. Besides MS hardware advances, quantitative metabolomics also requires extensive efforts in other analytical and bioinformatic methodology development. For a given MS platform, analytical method development focuses on laboratory practice, including sample handling, metabolome extraction, and data acquisition. In comparison, bioinformatic method development emphasizes computational data processing, such as data calibration, data curation, and statistical analysis. The subsequent chapters detail the development of analytical and bioinformatic solutions for quantitative metabolomics from improving metabolic coverage, analytical accuracy, analytical precision, and statistical analysis. Lastly, this thesis describes a metabolomics study of mouse brain regional differences in metabolism between males and females. Collectively my studies of quantitative metabolomics improve quantitative performance, deepen our knowledge of the MS-based quantification process, and facilitate the generation of confident biological conclusions.
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| Genre | |
| Type | |
| Language |
eng
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| Date Available |
2023-03-27
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| Provider |
Vancouver : University of British Columbia Library
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| Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
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| DOI |
10.14288/1.0428662
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| URI | |
| Degree | |
| Program | |
| Affiliation | |
| Degree Grantor |
University of British Columbia
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| Graduation Date |
2023-05
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| Campus | |
| Scholarly Level |
Graduate
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| Rights URI | |
| Aggregated Source Repository |
DSpace
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Rights
Attribution-NonCommercial-NoDerivatives 4.0 International