Thesis Topic Details

Topic ID:
3447
Title:
Analysis of alternative splicing in cancer
Supervisor:
Jason Wong
Research Area:
Bioinformatics, Genome informatics, Algorithms
Associated Staff
Assessor:
Bruno Gaeta
Topic Details
Status:
Active
Type:
R & D
Programs:
CS CE BIOM BINF SE
Group Suitable:
No
Industrial:
No
Pre-requisites:
A keen interest in bioinformatics and genomics is required for this project and a background in the same subjects would be desirable but not essential
Description:
It is well known that the expression of genes is altered in cancer cells. However, the extent to which alternate gene products, formed through the alternate splicing of RNA, is changed in cancer remains poorly understood. Although high-throughput sequencing (HTS) has generated vast amounts of raw genomics information on different cancers, a major limitation is the lack of suitable informatics tools to quantitatively analyse this data.

This project aims to develop an analysis platform that can accurately identify novel alternatively-spliced transcripts that are specifically present in blood cancer cells. Working closely in collaboration with molecular biologists and bioinformaticians, the student will develop tools to analyse HTS data that has recently been generated from cancer patients. The project has the potential to identify possible causes of blood cancer and guide future therapies.

Although the general field is bioinformatics, this project mainly involves software and algorithm development and does not require much knowledge of biology. Any necessary biology background can be quickly learnt on the job. This project is an ideal primer for a student who wishes to apply computational knowledge to one of the most exciting areas in current biology research.
Comments:
http://powcs.med.unsw.edu.au/research/adult-cancer-program/research-groups/bioinformatics
Past Student Reports
 
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