TORONTO—In the belief that the whole is greater than the sum of its parts, the Canadian Institute of Advanced Research (CIAR) recently announced the formation of new program that will analyze genetic networks as clues to human disease. The Genetic Networks Research Program will bring together scientists from across Canada and around the world, combining expertise in genetics, computational biology, statistical analysis and theoretical physics, to address the complexity of human biology.
The program is largely the result of the recent explosion in scientific data arising from high-throughput experimentation and genetic analysis of various organisms and human disease states. According to program director and University of Toronto researcher Dr. Brenda Andrews, this program could not have existed 10 years ago. "With more and more genetic sequencing data available, we are now in a position to make sense of all this information, and take our understanding of genetic networks to a whole new level," she says.
"Research this advanced and complex requires the time, expertise, and perspective from many people," adds Dr. Chaviva Hošek, CIAR president and CEO. "Our investment is large, but we believe the payoff is well worth it."
"CIAR receives funding from a combination of private and public funding—about half from the federal government, and then about a quarter each from the provinces and private donors, a combination of businesses, foundations, and individuals," explains Patchen Barss, CIAR director of communications. "We allocate funds to researchers in a variety of ways that give them the time and freedom to research and collaborate."
The advanced nature of the research to be performed by the Genetic Networks means that industry is unlikely to play much of a role in the initial phases of the program, Barss says. But CIAR makes a point of ensuring that the fundamental research comes to the attention of people doing more applied R&D.
In a November 2005 report by Frost & Sullivan, however, market analyst Katherine Austin spoke about the need for this type of resource integration to boost the uptake of bioinformatics and clinical informatics.
"A proteomics researcher should be able to cross-reference and study sequence databases, gene-expression data and structural data for a particular protein in one sitting," she says. "The difficulty is defining the applications that will be most useful to researchers in the future and which data standards and operating systems will prevail and thus should be supported."
The combination of resources undertaken by the Genetic Networks should be a key step in achieving these goals. "If you use the pipeline metaphor," Barss says, "we are the source of the flow of ideas, while industry applications are much further downstream."