Dhondalay, GKR, 2013. Systems biology of breast cancer. PhD, Nottingham Trent University.
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Abstract
Breast cancer, with an alarming incidence rate throughout the globe, has attracted significant investigations to identify disease specific biomarkers. Among these, oestrogen receptor (ER) occupies a central role where overexpression is a prognostic indication for breast cancer. The cross-talk between the responsible contenders of ER-associated genes potentially play an important role in the disease aetiology. Investigation of such cross talk is the focus of this thesis. The development of high throughput technologies such as expression microarrays has paved the way for investigating thousands of genes at a time. Microarrays with their high data volume, multivariate nature and non-linearity pose challenges for analysing using conventional statistical approaches. To combat these challenges, computational researchers have developed machine learning approaches such as Artificial Neural Networks (ANNs). This thesis evaluates ANNs based methodologies and their application to the analysis of microarray data generated for breast cancer cases of differing oestrogen receptor status. Furthermore they are used for network inferencing to identify interactions between ER-associated markers and for the subsequent identification of putative pathway elements. The present thesis shows that it is possible to identify some ER-associated breast cancer relevant markers using ANNs. These have been subsequently validated on clinical breast tumour samples highlighting the promise of this approach.
Item Type: | Thesis |
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Creators: | Dhondalay, G.K.R. |
Date: | 2013 |
Rights: | This work is the intellectual property of the author, and may be owned by the School of Science and Technology, Nottingham Trent University. You may copy up to 5% of the work for private study, or personal, non-commercial research. Any re-use of the information continued within the document should be fully referenced, quoting the author, title, university, degree level and pagination. Queries or requests for any other use, or if a more substantial copy is requested, should be directed in the first instance to the author of the Intellectual Property Rights. |
Divisions: | Schools > School of Science and Technology |
Record created by: | EPrints Services |
Date Added: | 09 Oct 2015 09:36 |
Last Modified: | 09 Oct 2015 09:36 |
URI: | https://irep.ntu.ac.uk/id/eprint/316 |
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