Kabir, Md Humayun (2018) Computational methods for identifying cell type, signalling pathways and gene regulatory networks. PhD thesis, Victor Chang Cardiac Research Institute and School of Medicine, Western Sydney University.
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Abstract
Due to the advancement of genetic technologies it is now possible to accurately and
simultaneously measure the expression levels of essentially all genes for species that have
had their genomes sequenced. A detailed molecular understanding of these gene expression
data will facilitate identification of new drug and cell therapy targets for disease treatment.
There are increasing amounts of genome-wide public gene expression data that provide
valuable information for the research community. The underlying hypothesis for this thesis is
that development of new bioinformatics methods for both cell type and signal pathway
characterization – that make use of public gene expression data – will facilitate application of
stem cells and their differentiated derivatives. Each chapter in this thesis had specific aims.
Chapter 1 presents a literature review that aimed to overview current bioinformatics tools
applicable to robust definition of stem cell and differentiated cell identity. Chapter 2 aimed to
develop a new tool (termed C3) for identifying unknown cell types based on their
transcriptional profile. Chapter 3 aimed to characterize a new populations of purified cells
(termed ROR1+ cells) obtained from differentiation of human pluripotent stem cells. Chapter
4 aimed to develop a new method (termed SPAGI) for predicting active signalling pathways
for any cell type, based on the cell’s transcriptome. Chapter 5 aimed to provide a large-scale
prediction (or blueprint) of signal pathway-mediated regulation of lens epithelial cell gene
expression. Lastly, the final chapter provides an overall reflection on the thesis combined
with perspectives on future work made possible as a result of the thesis.
| Item Type: | Thesis (PhD ) |
|---|---|
| Subjects: | R Medicine > R Medicine (General) |
| Divisions: | Faculty of Medicine, Health and Life Sciences > School of Medicine |
| Depositing User: | Repository Administrator |
| Date Deposited: | 26 Oct 2020 04:08 |
| Last Modified: | 26 Oct 2020 22:51 |
| URI: | https://eprints.victorchang.edu.au/id/eprint/1023 |
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