The last two decades have seen a major increase in the use of cryo-eleclron microscopy for virus reconstruction. Icosahedral virus reconstruction is particularly successful partly because the high symmetry of the structure can provide a guide to orient images via . for example. common lines. In this thesis. we introduce two improvements to t he icosahedral virus reconstruction methodology. Firstly. we propose a systematic probability-based orientation method to increase the accuracy of orientation. It will be shown that. relying on the statistical properties rather than the magnitudes of common-line residuals. the accuracy! can be improved substantially. Viruses such as adenovirus can be reconstructed straight- away without any model-based orientation refinement. Secondly_ we introduce a novel approach to identify icosahedral druses so that a) efficient icosahedral virus reconstruction methods can be used correctly on , viruses to achieve higher resolution" b) biologists ca better understand the structure and mechanism 0 1" ,viruses" This is done by decomposing common- line residuals into pair residuals and modelling them by normal mixture distributions. An innovative Markov chain Monte Carlo method. partition sampler. is design to efficiently estimate the number of components in the normal mixture distribution an hence help to identify the icosahedral viruses. The methodology ha'-e been tested on fixed viruses. Among these adenovirus. PRD1 and SFV are successfully identified as icosahedra viruses. and MMTV and HIV as non-icosahedral viruses.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:600228 |
| Date | January 2012 |
| Creators | Chen, Jian |
| Publisher | University of Oxford |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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