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UBC Theses and Dissertations
Development of bioinformatic solution to enhance metabolomics data quality and its application in plant research Zhang, Zixuan
Abstract
This thesis delves into the development and application of metabolomics, a discipline focused on the comprehensive study of metabolites within biological systems. The research is segmented into two interconnected parts: methodology development for metabolomics data processing and its subsequent application in plant stress physiology. The first project tackles the challenge of computational variation in untargeted metabolomics, which arises due to the incapability of data processing for complex LC-MS data. An in-depth exploration led to the identification of sources and causes of computational variation, followed by the development of novel methodologies to mitigate these challenges. These methodologies, including data processing parameter optimization and a machine learning program, successfully reduced computational variation, thereby enhancing the quantitative precision of untargeted metabolomics. The second segment of the thesis applies these methodologies to study the salinity stress response in Alfalfa (Medicago sativa L.). Comprehensive analysis of the plant's metabolic alterations, coupled with transcriptomics data, revealed significant pathways and mechanisms of salinity response. The integration of multi-omics data provided a deeper understanding of the complex interplay between genes and metabolites. The research advances the field of metabolomics, providing improved data processing methodology and valuable insights into plant stress physiology. Future work may expand these findings towards personalized medicine, disease diagnosis, and precision treatment.
Item Metadata
Title |
Development of bioinformatic solution to enhance metabolomics data quality and its application in plant research
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Creator | |
Supervisor | |
Publisher |
University of British Columbia
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Date Issued |
2023
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Description |
This thesis delves into the development and application of metabolomics, a discipline focused on the comprehensive study of metabolites within biological systems. The research is segmented into two interconnected parts: methodology development for metabolomics data processing and its subsequent application in plant stress physiology.
The first project tackles the challenge of computational variation in untargeted metabolomics, which arises due to the incapability of data processing for complex LC-MS data. An in-depth exploration led to the identification of sources and causes of computational variation, followed by the development of novel methodologies to mitigate these challenges. These methodologies, including data processing parameter optimization and a machine learning program, successfully reduced computational variation, thereby enhancing the quantitative precision of untargeted metabolomics.
The second segment of the thesis applies these methodologies to study the salinity stress response in Alfalfa (Medicago sativa L.). Comprehensive analysis of the plant's metabolic alterations, coupled with transcriptomics data, revealed significant pathways and mechanisms of salinity response. The integration of multi-omics data provided a deeper understanding of the complex interplay between genes and metabolites.
The research advances the field of metabolomics, providing improved data processing methodology and valuable insights into plant stress physiology. Future work may expand these findings towards personalized medicine, disease diagnosis, and precision treatment.
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Genre | |
Type | |
Language |
eng
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Date Available |
2023-09-28
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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 |
10.14288/1.0436920
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URI | |
Degree | |
Program | |
Affiliation | |
Degree Grantor |
University of British Columbia
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Graduation Date |
2023-11
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Campus | |
Scholarly Level |
Graduate
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Rights URI | |
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DSpace
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Rights
Attribution-NonCommercial-NoDerivatives 4.0 International