Proteomic and mass spectral data mining to search for biomarkers of pathogenic neisseria
Schmid, Oliver 2007. Proteomic and mass spectral data mining to search for biomarkers of pathogenic neisseria. PhD Thesis University of East London School of Health, Sport and Bioscience
Neisseria meningitidis causes over 1 million cases of meningitis and septicaemia annually. Currently available vaccines show only poor immunogenicity in children and do not induce immunological memory. The main focus of this study was on exploring the organism by mass spectrometry and 2-D GE to attempt to identify potential biomarkers and get a better understanding of the biology of N.
The technologies applied show great potential for future investigations into the subpopulations of this pathogen. Overall, the results demonstrated that future approaches to study the biology of this pathogen should be polyphasic, combining genomic and proteomic analyses to provide a more holistic overview of strains. Such an approach will likely enable new stable targets to be identified from which a
|Keywords||Meningitis and septicaemia; Biomarkers; Mass spectral data mining|
|Publication process dates|
|Deposited||16 Jan 2014|
This thesis supplied via ROAR to UEL-registered users is protected by copyright and other intellectual property rights, and duplication of any part of the material is not permitted, except for your personal use for the purposes of non-commercial research and private study in electronic or print form. You must obtain permission from the copyright-holder for any other use. Electronic or print copies may not be offered, for sale or otherwise, to anyone. No quotation from the thesis may be published without proper acknowledgement.
File Access Level
Registered users only
1views this month
0downloads this month