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Development of in silico framework to support pre-clinical model selection

School of Medicine, Dentistry and Biomedical Sciences | PHD
Funding
Unfunded
Reference Number
SMED-2201-1051
Application Deadline
None specified
Start Date
None specified

Overview

Pre-clinical models, including cell lines, are essential to modelling diseases and treatment response in the laboratory setting. In vitro or vivo model choice can be based on personal preference or laboratory custom. However, there is limited focus as to how well these models characterise their target systems. Yet, models, such as cell lines, can be subject to mislabelling and contamination. This project will develop an online tool that will test and  ‘match’ pre-clinical models against selected patient groups.

The first stage of the project will involve the curation of publicly-available datasets of human and pre-clinical cancer models, including both gene expression profiles and clinico-pathological data. A ‘soft’ integration method will be used to identify similarities and determine robustness of matches between pre-clinical models and patient groups. Patient groups will be stratified using different methods, including prognosis, molecular subtypes, pathways and clinico-pathological data.  The online tool will present ranked results across multiple datasets using meta-analytical techniques.

Project Summary
Supervisor

Dr Jaine Blayney

More Information

askmhls@qub.ac.uk

Research Profile


Mode of Study

Full-time: 3 Years


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