How Gary Bader Helped Meld Computer Science With Biology to Revolutionise Data Analysis and Become a World’s Top Cited Academic
Gary Bader learned to code as a young boy so he could play video games on a Commodore 64, the 1980s iconic home computer.
“Commodore 64 was really good because to play a video game you had to type commands first,” says Bader, a professor of computational biology at the University of Toronto’s Donnelly Centre for Cellular and Biomolecular Research. ”It was a good incentive to learn how things worked.”
Bader never stopped figuring out how things worked. Leading a team of two dozen computational experts, he is world-renowned for his research that uses machine learning to decode one of biology’s greatest mysteries— how genes influence health.
“The ultimate goal of our research is to take all the big human biology data that exists and use it to make predictions about personal health,” says Bader, who is also a professor in U of T’s Departments of Molecular Genetics and Computer Science, an associate member of the Sinai Health System's Lunenfeld-Tanenbaum Research Institute and holds Ontario Research Chair in Biomarkers of Disease.
Computational advances have revolutionized biomedical research allowing researchers like Bader to gain meaningful insights from a sea of data. But Bader has also played a key role in driving these innovations.
While still a graduate student, in the late 1990s in Christopher Hogue’s lab, then at the Lunenfeld-Tanenbaum Research Institute, Bader wrote a software that would help change how researchers visualize large scale molecular data. Genomic technologies that were emerging at the time enabled researchers to simultaneously study thousands of genes and their protein products. And while there was a growing awareness that the clues to health and disease lie in the way proteins and other molecules interact with each other, there was no good way to illustrate these networks.
"The ultimate goal of our research is to take all the big human biology data that exists and use it to make predictions about personal health" - Professor Gary Bader
By borrowing from graph theory, used in mathematics for over a century to study a set of nodes and connections between them, Bader wrote one of the first computer systems for storing and depicting interactions between different proteins. The software not only organized the data into a network, but it also placed molecules working closely together into tight clusters. This allowed researchers to make assumptions about, say, genes they knew little about based on their positions in the network.
Called BIND, for Biomolecular Interaction Network Database, Bader’s software attracted millions in investments from government and industry. It also helped establish Toronto as one of the few places in the world with expertise in the new field of network biology helping it become a leading biomedical research hub it is today.
In space of a month, Bader’s graduate research was part of two papers in Science and one in Nature, a feat most academics can only dream of. These were first in a string of high-profile publications that make Bader one of the world’s most influential researchers in his field. Judged by his papers’ citation rate, a measure of how many times other research publications refer to his work, Bader is among the top one percent most cited academics globally, as announced today by Clarivate Analytics, a data company previously owned by Thomson Reuters. Bader made the cut before in 2014.
“It’s nice to see that our team’s work has impact,” says Bader for being on the list.
Chan is the director of the Institute for Biomaterials and Biomedical Engineering and a professor in the Departments of Materials Science and Engineering, Chemistry and Chemical Engineering and Morris is a professor in the Departments of Molecular Genetics and Computer Science and a faculty at Vector Institute for Artificial Intelligence.
More recently, Bader’s team helped create the first map of liver cells at the molecular level to serve as a roadmap for developing future cell therapies for liver disease.
The findings are part of the Human Cell Atlas, a large international effort to reveal the molecular makeup of all cells in the human body with Bader as the Canadian representative on the consortium’s organizing committee. The project was made possible by the new technology of single cell genomics which lets researchers see which genes are switched on in individual cells in the body.
Watch this Research2reality video with Bader explaining how single cell genomics is helping researchers understand how the human body works:
Another area of Bader’s research is cancer. A few years ago, he helped identify a drug target in the brain tumour of an nine-year-old boy, in a stark example of how computational research can impact health in real life. Working with Dr. Michael Taylor, a neurosurgeon at the Hospital for Sick Children, the team was able to source a drug compound targeting a cellular mechanism which Bader’s algorithm predicted is critical for the tumour. The drug worked and is now being tested in more patients as part of two clinical trials.
One day he hopes to be able to similarly help patients with breast cancer, as well as with glioblastoma, an aggressive form of brain cancer that strikes adults and for which the prognosis remains grim at around 15 months survival after diagnosis.
“My dream is to help find new treatments for glioblastoma because nothing has changed the survival of that cancer for many years” says Bader who, along with another Donnelly colleague, Professor Amy Caudy, is on the Stand up to Cancer Canada’s Brain Dream Team led by Drs. Peter Dirks of SickKids and Samuel Weiss of University of Calgary. “We have so much data, we’re getting lots of new interesting insights and I am very excited about spending a number of years really thinking about that,” he says.
His video gaming days may be long over, but for Bader, the thrill of figuring out of how things work shows no sign of stopping.
Follow us on Twitter to keep up with Donnelly Centre news.