Document Type Master's Dissertation Author Bezuidt, Keoagile Ignatius Oliver email@example.com URN etd-08162010-143700 Document Title Development of novel computational tools based on analysis of DNA compositional biases to identify and study the distribution of mobile genomic elements among bacteria Degree MSc Department Biochemistry Supervisor
Advisor Name Title Prof F Joubert Co-Supervisor Dr O Reva Supervisor Keywords
- mobile genomic elements
- computational tools
Date 2010-04-28 Availability unrestricted Abstract
Horizontal gene transfer, well characterized as the transfer of genomic material between organisms contributes hugely in the evolution and speciation of bacteria. The transfer of such material brings about bacteria that are virulent and also in possession of genes that render them resistant to antibiotics. This helps to spread about and recombine genes of their kind to other bacteria. Horizontally acquired genomic elements exhibit compositional features that are deviant from the rest of the other genes in a recipient genome. They possess features such as unusual GC%, atypical codon usage, oligonucleotide usage bias and direct repeats at their flanks that can be used to distinguish them from native genes in a genome. This work focused on the developments of statistical and computational methods to aid with the detection of genes that have undergone horizontal transfer, to help track down genes that could be of medical and environmental importance. Therefore, SeqWord Gene Island Sniffer (SWGIS), a statistically driven computational tool for the prediction of genomic islands, and GEI-DB, a comprehensive database of horizontally transferred genomic elements were established. The SWGIS tool allows the precise predictions of precise inserts of horizontally acquired gene clusters in prokaryotic genomic sequences. Thus, the GEI-DB stores all the foreign genomic inserts that have been detected in the study, together with their annotations and evolutionary measures, such as groups of genomic islands that share similarities in DNA and amino acids features.
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Please cite as follows:
Bezuidt, KIO 2009, Development of novel computational tools based on analysis of DNA compositional biases to identify and study the distribution of mobile genomic elements among bacteria, MSc dissertation, University of Pretoria, Pretoria, viewed yymmdd < http://upetd.up.ac.za/thesis/available/etd-08162010-143700/ >
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