Bioinformatics, Health and Medical Analytics
Program Leaders: Professor Jinyan Li and Professor Patricia Davidson
Research in this stream is driven by the big data accumulated in biological, health and medical services. We deliver evidence-based bioinformatics, health and medical analytics research solutions. This theme looks at new hypotheses, benchmarking, cause and effect analysis and the active management of disease, patients and treatments. Our work is undertaken in-house and in collaboration with major industry organisations.
Areas of research focus include:
- Detection of signature patterns and tandem repeats in genomic sequences
- Rule discovery and disease gene identification from miRNA and mRNA expression data
- B factors, O-ring hypothesis and water theories for protein binding hotspots prediction
- Substructure modules detection in protein interaction networks
- Conformational B-cell epitope prediction
- Antibody-antigen interactions in infectious diseases such as H1N1 influenza A
- Big medical and health data analytics and decision-support
- Data-driven, evidence-based health and medical benchmarking, hypothesis generation, and verification
- Instant detection and early prediction, warning, and intervention in relation to the misuse, underuse and overuse of health services and/or resources and fraud
- Performance evaluation, review and optimisation of health service resources, procedures, processes and treatments and service delivery objectives
- Multiple sources of health, medical and public data analysis
- Systematic approaches for analysing interplay between multiple factors of patient, provider and health system aspects
- Patient behaviour and sentiment analysis and personalized service and treatment recommendation
- Early warning and prediction of healthcare problems
- Risk rating and factor analysis of high-risk cases, areas and scenarios