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Computational detection of recombination in the Hepatitis B Virus genome

Alexidis, F; (2005) Computational detection of recombination in the Hepatitis B Virus genome. Doctoral thesis , UCL (University College London). Green open access


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Hepatitis B Virus (HBV) is the causative agent of the disease of hepatitis B in humans. More than 2 billion people are infected worldwide, 350 million of which are chronic carriers. Many attempts have been made and there is very wide ongoing worldwide research towards the development of treatments and even therapy of that disease, namely, antiviral therapies and vaccines are currently available to patients. However, HBV has a marked ability to develop resistant strains, not only due to the introduced natural selected mutations, but also due to the phenomenon of recombination and thus, remain threat for human health. A number of computational methods are currently available to look for recombinant strains, but all have problematic areas. A new attempt for recombination detection has been made by the implementation of the Reel which, in combination with the program LOHA, is shown in this report to significantly detect recombination events. Reel was translated from the prograrnming language Perl, where it was initially written, in C++ and that version was found to be significantly faster. A list of previously reported recombinant sequences were analyzed by Reel and with the previously developed Subtype AnalyseR (STAR) and the comparison showed that Reel analysis algorithm was able to detect almost all the previously reported as putative recombinants. Thus, the translation of Reel from Perl to C++ combines the good recombination detection ability of Reel algorithm, with the increased speed of C++ architecture and can aid the recombination detection research field.

Type: Thesis (Doctoral)
Title: Computational detection of recombination in the Hepatitis B Virus genome
Open access status: An open access version is available from UCL Discovery
Language: English
Additional information: Thesis digitised by ProQuest.
UCL classification: UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health
URI: https://discovery.ucl.ac.uk/id/eprint/1568028
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