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Theses and Dissertations
This collection contains theses and dissertations of graduate students of the University of Alberta. The collection contains a very large number of theses electronically available that were granted from 1947 to 2009, 90% of theses granted from 2009-2014, and 100% of theses granted from April 2014 to the present (as long as the theses are not under temporary embargo by agreement with the Faculty of Graduate and Postdoctoral Studies). IMPORTANT NOTE: To conduct a comprehensive search of all UofA theses granted and in University of Alberta Libraries collections, search the library catalogue at www.library.ualberta.ca - you may search by Author, Title, Keyword, or search by Department.
To retrieve all theses and dissertations associated with a specific department from the library catalogue, choose 'Advanced' and keyword search "university of alberta dept of english" OR "university of alberta department of english" (for example). Past graduates who wish to have their thesis or dissertation added to this collection can contact us at erahelp@ualberta.ca.
Items in this Collection
- 1Genetics--Technique
- 1Genomic prediction
- 1Genotype imputation
- 1Lean Manufacturing
- 1Missing observations (Statistics)
- 1Nucleotide sequence
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Fall 2019
The manufacturing sector is of importance to Canada’s economic vitality. However, given the phenomenon of globalization, low trade barriers, and advances in technology, there has been a decline in manufacturing’s share of the Canadian economy. Today, Canadian manufacturing companies are striving...
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Fall 2011
High-throughput single nucleotide polymorphism (SNP) genotyping technologies conveniently produce large SNP genotype datasets for genome-wide linkage and association studies. Various factors, from array design and hybridization, can give rise to a certain percentage of missing calls, and the...
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Fall 2017
In this dissertation, I focus on the study of genotype imputation in population data. Genotype imputation is a process of inferring missing values for genotype data and has been extended to predicting “untyped” genotypes for samples in low-density chips with a reference population assayed using...