Bioinformatics is the use of advanced computer modelling and mathematical algorithms to predict disease risk and inform clinical practice regarding individual biological data.
With the improvement of computing technologies in recent times, the capabilities for analysing complex data have become more advanced, and more accessible.
In the human genome, there are over 3 billion pairs of amino acids which code for an estimated 25,000 proteins and countless other non-coding molecules such as miRNA, whose functions are only just being uncovered.
Given the increasing affordability of genetic testing and the modern culture of “big data”, enormous amounts of biomedical data can be generated over a relatively short space of time and with relatively low cost. However, it is only with advanced analytical methods that the relevant information can be identified within these data sets and put to good use.
Today, qualifying patients are able to have their genome screened or tested simply by providing a blood, skin, hair or saliva sample, depending on the test to be performed. This capability for quick and reliable genetic testing has opened the floodgates for high volumes of genetic data on individual patients. Bioinformatics allows meaningful interpretation of that data and unlocks the potential for personalised medicine where treatments could potentially be tailored to each individual patient.
Researchers in the HMRI information based medicine research program have made a number of important findings in disease areas such as dementia and Alzheimer’s disease, inflammatory bowel disease, multiple sclerosis, childhood absence epilepsy and even schizophrenia.
In 2012, research led by the co-director of the HMRI information based medicine program, Professor Pablo Moscato, found a suite of proteins in the blood that could successfully detect the likelihood of developing Alzheimer’s disease before any symptoms developed with over 90% accuracy. This group have also identified important genetic biomarkers for multiple sclerosis which can help to determine a patient’s susceptibility for developing the disease.
"One of the most fulfilling aspects of our work in bioinformatics is the perception that the outcomes are for the common good. Even when you are doing something that may look like a tiny incremental step on the existing knowledge, you have the satisfaction that it will contribute to improving someone's health or to have a better understanding of the cause of a disease", explains key researcher Associate Professor Regina Berretta at the University of Newcastle.