Why computational biology?
Computational Biology is the science of analysing large collections of biological data, such as blood or cervical screening samples, or genetic information. It allows millions of data points to be gathered from just a few samples. This data is then used to find patterns that allow us to spot whether certain molecules and biological pathways cause gynaecological cancers. This type of research can help us to understand how our DNA and the things that alter our DNA relate to cancer development.
Since the introduction of computational biology to the UCL research teams in 2019, it has brought significant progress to various research projects.
The ultimate vision was to develop a single test that will spot who is at risk of any of these four cancers: breast, ovarian, cervical, and womb cancer. Computational biology played a key role in the development of this test, and the initial results of the research have been really promising. In practice this test could personalise screening and treatment prevention for breast, ovarian, cervical, and womb cancers, with the potential to save thousands of lives every year.
It has also increased the team’s understanding of how normal, healthy cells transform into cancer cells, a process called ‘carcinogenesis’. This knowledge can open up new areas of research in the prevention of gynae cancers.
Computational biology is essential to the UCL team’s research, understanding cancer development, predicting risk of cancer, and early detection, all with the ultimate goal of the prevention of gynaecological cancers.