Development of novel computational tools based on analysis of DNA compositional biases to identify and study the distribution of mobile genomic elements among bacteria

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dc.contributor.advisor Joubert, Fourie en
dc.contributor.advisor Reva, Oleg N. en
dc.contributor.postgraduate Bezuidt, K.I.O. (Keoagile Ignatius Oliver)
dc.date.accessioned 2013-09-07T11:09:14Z
dc.date.available 2010-08-16 en
dc.date.available 2013-09-07T11:09:14Z
dc.date.created 2010-04-28 en
dc.date.issued 2010-08-16 en
dc.date.submitted 2010-08-16 en
dc.description Dissertation (MSc)--University of Pretoria, 2010. en
dc.description.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. Copyright en
dc.description.availability unrestricted en
dc.description.department Biochemistry en
dc.identifier.citation 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://hdl.handle.net/2263/27297 > en
dc.identifier.other E10/403/gm en
dc.identifier.upetdurl http://upetd.up.ac.za/thesis/available/etd-08162010-143700/ en
dc.identifier.uri http://hdl.handle.net/2263/27297
dc.language.iso en
dc.publisher University of Pretoria en_ZA
dc.rights © 2009, University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. en
dc.subject Mobile genomic elements en
dc.subject Computational tools en
dc.subject UCTD en_US
dc.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 en
dc.type Dissertation en


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