Computational Approaches for Improved Identification, Quantitation, and Interpretation of Mass Spectrometry-based "omics" Data
Author | : Nicholas William Kwiecien |
Publisher | : |
Total Pages | : 0 |
Release | : 2016 |
ISBN-10 | : OCLC:1101986960 |
ISBN-13 | : |
Rating | : 4/5 ( Downloads) |
Download or read book Computational Approaches for Improved Identification, Quantitation, and Interpretation of Mass Spectrometry-based "omics" Data written by Nicholas William Kwiecien and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The research described in this dissertation presents novel computational algorithms and strategies for (1) improving the assignment of molecular identities to analytes profiled by high-resolution gas chromatography-mass spectrometry (GC/MS), (2) performing relative quantitation of large sets of metabolites across expansive sets of mass spectrometry data files, (3) disseminating processed mass spectrometry data and post hoc statistical results in web-based platforms, and (4) monitoring mass spectrometer performance via a web-based data processing and analysis tool. An overview of the aforementioned computational strategies and developed software tools is presented in Chapter 1. A novel algorithm for leveraging accurate mass--afforded by high-resolution GC/MS systems--to discriminate between putative identifications assigned to profiled small molecules is described in Chapter 2. In Chapter 3, an algorithm and accompanying software suite designed to enable untargeted quantitation of small molecules across expansive sets of raw GC/MS data files is described. In Chapter 4, these algorithms are employed as part of a larger study wherein 174 single gene deletion strains of yeast were comprehensively profiled at the proteomic, metabolomic, and lipidomic levels. These multi-omic data were then integrated through various analysis planes in order to define functions of uncharacterized mitochondrial proteins. Chapter 5 details numerous web-based data visualization utilities developed for various projects designed to enable researchers to more rapidly interrogate MS data sets at depth. In Chapter 6, the development of a web-based mass spectrometry data deposition, processing, and visualization tool for automated quality control analysis is described.