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Permanent link (DOI): https://doi.org/10.7939/R33W7D

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Developing bioinformatics tools for metabolomics Open Access

Descriptions

Other title
Subject/Keyword
metabolomics
metabolite set enrichment analysis
statistical analysis
metabolic pathway analysis
two dimensional NMR
bioinformatics
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Xia, Jianguo
Supervisor and department
Wishart, David (Computing Science)
Examining committee member and department
Gallin, Warren (Biological Sciences)
Li, Liang (Chemistry)
Deyholos, Michael (Biological Sciences)
Greiner, Russ (Computing Science)
Pavlidis, Paul (Psychiatry, University of British Columbia)
Department
Department of Biological Sciences
Specialization

Date accepted
2011-07-29T18:32:54Z
Graduation date
2011-11
Degree
Doctor of Philosophy
Degree level
Doctoral
Abstract
Metabolomics aims to study all small-molecule compounds (i.e. metabolites) in cells, tissues, or biofluids. These compounds provide a functional readout of the physiological, developmental, and pathological state of a biological system. The field of metabolomics has expanded rapidly over the last few years with increasing applications to disease diagnosis, drug toxicity screening, nutritional studies and many other life sciences. However, significant challenges remain in both collecting and understanding metabolomic data. The central objective of my thesis project is to develop novel bioinformatic tools to address some of the key computational challenges in metabolomic studies. In particular, my research is focused on three areas: (i) compound identification from complex biofluids, (ii) processing and statistical analysis of metabolomic data, and (iii) functional interpretation of metabolomic data. In addressing these issues I have developed a number of efficient and user-friendly software tools, including MetaboMiner, MetaboAnalyst, MSEA and MetPA. Each of these software packages has required the development of novel algorithms, novel interfaces or the implementation of novel analytical concepts. MetaboMiner ( http://wishart.biology.ualberta.ca/metabominer
) is a standalone Java application for compound identification from 2D NMR spectra of complex biofluids. Based on a novel adaptive search algorithm and specially constructed spectral libraries, MetaboMiner is able to automatically identify ~80% of metabolites from good quality NMR spectra. MetaboAnalyst ( http://www.metaboanalyst.ca
) is a web-based pipeline for metabolomic data processing, normalization, and statistical analysis. This application is based on a novel framework that combines the statistical and visualization power offered by R ( http://www.r-project.org
) with an enhanced graphical user interface enabled by Java Server Faces technology. It is currently the most comprehensive and popular data analysis web service in metabolomics. MSEA or metabolite set enrichment analysis ( http://www.msea.ca
) represents a novel application of the gene set enrichment analysis technique to metabolomics. In particular, MSEA is a web application for the identification of biologically meaningful patterns through enrichment analysis of quantitative metabolomic data. To create MSEA, I assembled a unique database of ~6300 groups of biologically related metabolites with association data on diseases, pathways, genetic traits, and cellular or organ localization. MetPA ( http://metpa.metabolomics.ca
) is a web-based tool for metabolic pathway analysis. It integrates functional enrichment analysis and pathway topology analysis through a novel Google-map style network visualization system. MetPA currently supports the analysis of ~1200 KEGG metabolic pathways for 15 model organisms.

Language
English
DOI
doi:10.7939/R33W7D
Rights
License granted by Jianguo Xia (jianguox@ualberta.ca) on 2011-07-28T06:24:53Z (GMT): Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of the above terms. The author reserves all other publication and other rights in association with the copyright in the thesis, and except as herein provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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