Biomedical Computing > Queen's School of Computing

Biomedical computing research is developing tools that enable the biomedical community to collect, analyze, model, simulate and share data on human health and disease. It does so by uniting the diagnostic, investigative and patient-centered approach of medical science with the power, speed and problem-solving capabilities of leading-edge computing. It already shows the potential for a substantial impact on the most significant challenges facing efforts to improve human health and well-being.

Modern biomedical advances – from genomics to imaging to proteomics – rely on computing infrastructure and expertise to make sense of, draw conclusions from, and apply in practice the massive amount of information that is collected on human health.

Research Topics

Bioinformatics: An interdisciplinary field, bioinformatics combines computer science, biology, pharmacology, information engineering, mathematics and statistics to analyze and interpret biological data. Bioinformatics research leverages vast datasets to solve problems in areas such as gene sequences, protein structures, molecular evolution, disease mechanisms, and drug testing, and plays a key role in the emerging area of ‘personalized medicine.’
Image-guided surgery: IGS helps surgeons to perform safer and less-invasive procedures by using surgical instruments in conjunction with medical imaging. IGS systems use cameras or electromagnetic fields to help orient the surgeon by providing three-dimensional images of surgical instruments relative to the patient’s anatomy. IGS technology helps to shorten operating times, decrease incision size and reduce a procedure's invasiveness, all of which contribute to better patient outcomes and quicker recovery. It also provides new options for patients with multiple medical problems, patients who may not be able to tolerate invasive surgeries, and patients whose conditions in the past might have been considered inoperable.