The Centre for Bioinformatics, Biomarker Discovery and Information-Based Medicine is committed to shortening the process of obtaining novel discoveries to achieve distinctively better outcomes in clinical practice and translational individualised medicine

Priority Research Centre for

About us

The Priority Research Centre for Bioinformatics, Biomarker Discovery and Information-Based Medicine (CIBM) is committed to shortening the process of obtaining novel discoveries to achieve distinctively better outcomes in clinical practice and translational individualised medicine.

Established in 2006, CIBM is a central interdisciplinary hub of the university and many of its researchers are part of the Hunter Medical Research Institute's Information-Based Medicine Program.

CIBM collaborates and obtains funding from several types of partnerships. It has attracted contract research from the National Institute of Health (USA), as well as from the Australian Research Council, the National Health and Medical Research Council and other funding bodies such as the National Breast Cancer Foundation. It has also attracted significant philanthropic corporate and private funding over the last years. 

What is Bioinformatics?

CIBM researchers master advanced and powerful computer technologies which allow them to extract meaningful information from large-scale datasets.

The core aim of CIBM is to change worldwide practices via new methods for smart information use.

Bioinformatics is a new interdisciplinary scientific field that combines Computer Science, Applied Mathematics and the Life Sciences to become the "first defence" against the deluge of data in the 21st century. The novel methodologies are also being applied to other big data-driven projects in other areas of research and development.

Biomarkers and creation of novel diagnostic tests

Of the many health challenges of this century, none are more pressing than the field of finding biological markers (biomarkers) that could lead to the introduction of reliable early detection tests (for instance in cancer and neurodegeneration).  

Mathematical and computational expertise is put to the limit as the number of possible markers that are measured with current technologies can easily surpass the figure of one million for a single individual sample. At CIBM the researchers employ new statistical methods to investigate each marker individually. In addition, they are world-experts in the area of combinatorial optimisation, the field of Applied Mathematics that deals with finding the best solutions when you have a finite but hugely large set of possibilities. Their unique knowledge allows them to discover panels of biomarkers which, when used together, lead to the development of tests that show higher accuracies than those of existing ones.  

Personalised information-based medicine

CIBM's focus is on personalised medicine, which aims to individualise patient treatment by maximising the benefits and minimising the adverse side effects.

 In a few years time, all known genetic risk factors for diseases could be routinely determined at birth. Using large-scale molecular interrogation methods, powered by advances in Mathematics and Computer Science, CIBM's work aims at identifying particular disease subtypes. This knowledge benefits patients as it would allow the guidance towards the best available treatment for each individual patient.

Outcomes of patient-tailored treatments will enable the development of new diagnostic approaches and drug designs that specifically target aberrant molecular pathways present in diseased cells with minimal interference on healthy ones. This is the promise of personalised information-based medicine.

Research themes

  • Large-scale data analytics
  • Predictive analytics
  • Artificial intelligence and pattern recognition
  • Supercomputing and multi-objective optimisation
  • Biotechnology and "-omics" (genomics, proteomics, metabolomics)

Key achievements

  • Identified a blood protein panel to recognise people in the early stages of Alzheimer's before symptoms appear. Read more...
  • Introduced a hallmark of cancer based on the changes of information theory quantifiers. Read more...
  • Proved the usefulness of an information theory-driven methodology by applying the technique to the identification of Alzheimer's Disease biomarkers. Read more...
  • Founded and organized the Inaugural Biomarker Discovery Meeting at Shoal Bay (2010). Read more...
  • Identified new multiple sclerosis susceptibility loci on chromosomes 12 and 20 ( Nature Genetics 2009). Read more...
  • Developed the first transcription factor map that can explain most of the gene expression variation observed in the gene expression molecular signatures for relapse remitting, primary progressive, and secondary progressive multiple sclerosis. Read more...
  • Developed a novel mathematical model, and an associated solution procedure based on combinatorial optimization techniques, to identify optimal drug combinations for cancer therapeutics. Read more...
  • Using a panel of abundances 120 signalling proteins on archived plasma samples, developed a novel mathematical method for biomarker discovery that led to the five-protein biomarker molecular signature for clinical Alzheimer's disease and developed classifiers that predict with 96% total accuracy the onset of the illness. Read more...
  • Developed the first method to distinguish childhood absence epilepsy from controls by the analysis of their background. Read more...