A Computational Approach for SNP Discovery
| dc.contributor.advisor | Matukumalli, Lakshmi | |
| dc.contributor.author | Al-Razgan, Othman | |
| dc.creator | Al-Razgan, Othman | |
| dc.date | 2013-08 | |
| dc.date.accessioned | 2014-09-18T18:24:13Z | |
| dc.date.available | 2014-09-18T18:24:13Z | |
| dc.date.issued | 2014-09-18 | |
| dc.description.abstract | The advent of the next-generation sequencing has revolutionized the ability of cattle genomics researchers to sequence many animals from a wide diversity of cattle breeds enabling extraction of high resolution genotypic data. Using these data to understand the relationship between the phenotypes and genotypes will enable significant improvements in food production and animal health. However the existing software methods for analyzing the sequence data and SNP discovery are not flawless and pose as a restriction for further research. The general objective of this dissertation is to equip the genomics researchers such as those working in Cattle with advanced computational tools and techniques, to utilize the ever amplifying accessibility of genome sequence in an effective manner. | |
| dc.description.note | This work was embargoed by the author and will not be available until August 2014. | |
| dc.identifier.uri | https://hdl.handle.net/1920/8933 | |
| dc.language.iso | en_US | |
| dc.rights | Copyright 2013 Othman Al-Razgan | |
| dc.subject | Phenotypes | |
| dc.subject | Genotypes | |
| dc.title | A Computational Approach for SNP Discovery | |
| dc.type | Dissertation | |
| thesis.degree.discipline | Bioinformatics and Computational Biology | |
| thesis.degree.grantor | George Mason University | |
| thesis.degree.level | Doctoral | |
| thesis.degree.name | PhD in Bioinformatics and Computational Biology |