Single-cell data analysis of hepatocellular carcinoma patient samples

Single-cell data analysis of hepatocellular carcinoma patient samples

Advisor/s

A/Prof Ulf Schmitz, A/Prof Lionel Hebbard, Dr Siyuan Wu

College or Research Centre

College of Medicine & Dentistry; College of Public Health, Medical & Veterinary Science

Summary of Project

We are working on a project that leverages advanced technology to study individual cells and their genetic information. This technology helps us understand the differences between cells, especially in cancer research. We're focusing on a type of sequencing that allows us to examine the entire length of gene transcripts in single cells. Our goal is to create a specialized computer pipeline for analysing this specific type of genetic data. This program will help us see how different versions of genes are expressed in individual cells. In particular, we want to compare these patterns in cancerous and normal tissues to find potential genetic factors driving the disease. We will apply this program to data from liver cancer samples, specifically those removed from patients at Townsville University Hospital. The samples were sequenced using the latest technology, allowing us to gain valuable insights into the genetic aspects of hepatocellular carcinoma

Key Words

Bioinformatics; Next Generation Sequencing; Tumour Biology

Would suit an applicant who

has a background in bioinformatics, computational biology, computer science, biomedical science, or a related field. This project is suitable for doctoral or master students. Prior experience in Bash and R programming would be very helpful.

Updated: 18 Jan 2024