Use this URL to cite or link to this record in EThOS:
Title: The elucidation of immunological and oncological transcriptomic signatures using translational ontologies and next-generation sequencing
Author: Deonarine, Andrew
ISNI:       0000 0004 5989 0669
Awarding Body: University of Cambridge
Current Institution: University of Cambridge
Date of Award: 2014
Availability of Full Text:
Access from EThOS:
Full text unavailable from EThOS. Please try the link below.
Access from Institution:
Understanding the large amounts of information produced by next-generation sequencing requires the comprehensive integration of biological knowledge, appropriate statistical frameworks, and computational models. In this work, a series of computational approaches and analyses are presented which outline a path from raw data to an understanding of biological regulation, disease pathogenesis, and mutational behaviour. The first chapter, “The Bioinformatics of Next Generation Sequencing” consists of the biological and computational background to next-generation sequencing. The next chapter, called “Ontology-Driven Investigation of the Immunome and Diseasome” consists of a description of the biomedical ontology with immunological functional annotations, and comprehensive disease-gene relationships. In chapter 3, “An Ontology-based Pipeline for Transcriptomic Analysis,” the computational approaches to next-generation sequencing will be integrated with the ontologies created in chapter 2. Here, a novel pipeline will be presented which encapsulates quality control, normalization, quantification, differential expression analysis, and functional annotation. This pipeline was tested with a set of transcriptomic data and corresponding proteomic data, facilitating the exploration of the relationship between these two datasets. Chapter 4, “Transcriptomic Signatures in Oncology and Immunology,” consists of two parts. First, a novel ontology-based barcoding algorithm was developed, and a murine pancreatic cancer model was analyzed to identify key pancreatic cancer genes. A pharmaceutical treatment candidate was also identified and biologically validated in a mouse model. In the second part of the chapter, a similar method was used to understand the role of Foxp3 architecture in immune system biology. These methods will then be framed in the context of broader biological and clinical applications. From these oncological and immunological analyses, a “central dogma” of transcriptomic expression patterns can be derived. In chapter 5, key conclusions and future directions will be discussed in more detail, and the translational implications of the pipeline and ontology explored.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral