How scientists are relying on the data modelling and analytical skills of computers
Computational biology combines the fields of data analysis and scientific discovery. Computer data is becoming more important than ever in science, as it gives scientists access to incredible analytical potential. In the field of biology, experts are using data analysis to explore everything from genetic sequences, cell populations, and molecule samples. This is known as computational biology.
A relatively broad concept, computational biology is an umbrella term for any biological study that involves data, statistics or modelling. Scientists can use computer processing facilities to make predictions about biological functions, and to make new discoveries from the data they already have. It is a tool that is equally powerful for making connections or conclusions that no one else has spotted before as enabling scientists to realise that things don’t quite work in the way they thought.
Computational biologists rely on computer software to test their data. Just as they would check and verify the results of their experiments in the physical world, scientists using code for computer analysis also run positive and negative controls. Whether they write their own code or adapt that of others, their knowledge of biology is vital when interpreting the results. Computational biologists are both scientists and computer specialists. Whilst they might use computers to process their data, expert scientific knowledge is required to make sense of the results.
Recent applications of computational biology have led to important advances in the scientific world. From analysing big data to tackle cancer, modelling our genes, and finding previously unknown natural antibiotics, the combination of computer technology with biology is leading to some increasingly impressive results.