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Ask someone to tell you the story of the blind men and the elephant, and they'll tell you a tale of six men, each of whom touched a different part of an elephant, unable to see what their hands were resting on. Asked to describe what they had touched, the man who felt the side of the elephant said, "I touched a wall," and the man who felt the elephant's tusk said, "I touched a spear." The six men argued among themselves--was it a snake, a cow, a piece of rope? Only when they worked together, sharing their different ideas and experiences, were they able to discover the truth.

Well, it seems as if scientists across the world are increasingly getting the point of that story. They are expanding their communication across fields, telling one another about their part of the elephant. The result is the formation of new, interdisciplinary scientific fields, such as bioinformatics, that are painting expanded pictures of the world around us, thanks to the collective efforts of diverse groups of researchers.

We describe our field as "pathogen bioinformatics," an area in which traditional microbiology and computer science intersect in the study of a variety of infectious diseases. This dual approach is very powerful, allowing us to analyze and prioritize the large amount of data provided by bacterial genome-sequencing projects, to rapidly identify features unique to particular pathogens (infectious disease-causing agents), and to rationally design vaccines and antibiotics to combat them. In addition, we work with a larger group of researchers in the new area of "pathogenomics," which involves using microbiology, evolutionary theory, computer science, medical genetics, and genomics to study how infectious disease agents interact with humans and then develop new approaches to manipulate these interactions to our benefit.

Many people are surprised when they learn that we carry out most of our research on a computer, particularly because the majority of topics that we work on (e.g., bacterial protein localization, infectious disease evolution, and host-pathogen interactions) sound pretty biological. The fact is, however, that computer-based techniques are becoming so prevalent in the molecular biology and microbiology worlds that they're virtually a prerequisite to most lab bench work.

With that said, most biologists have not had significant training in the computer sciences, or at the interface between biology and computer science, to undertake the more sophisticated computer analyses that may reveal additional genuinely novel insights. By using our knowledge of these fields, we are able to store, display, and analyze large amounts of genetic data in novel ways, presenting these data to other biologists and using the data ourselves to gain insights into how to prevent or treat infectious diseases. By using computational techniques, we can rapidly narrow down areas of research focus, saving us valuable bench time and hinting at what approaches and techniques might work best.

We are lucky to be able to work with a diverse array of collaborators. Our research brings us into contact with people in diverse fields, from computer science to mathematics and statistics to history. Every meeting with them opens our eyes to new ideas and new methods. Their input has helped our research immensely, and they benefit by better understanding what biological problems are worth studying using their research approaches, and why. The benefits of such collaborative interdisciplinary research are clear--"two heads are better than one" says it best--but it isn't without its problems. For example, two researchers working in different fields might have to get over their initial shyness and admit they don't know a lot about each other's area.

One of the most fascinating issues we've encountered is the notably different ways of thinking that typically characterize biologists and computer scientists. The biologist gathers knowledge, will often describe his or her work as if telling a story, strives to draw conclusions and construct models, and appreciates that exceptions are just as common as rules in our biological world. Compare this to the logic and process-oriented computer scientist, for whom rules and optimization are the goals, and you have the potential for miscommunication. The two groups, given the same problem, will ask different questions, pick up on different details, use different metaphors to describe the problem, and come into the situation with different assumptions.

We have found, though, that this is where the strength of interdisciplinary research shows its full potential. Mixing such different ways of thinking is a great way to stimulate the generation of new approaches to a problem that neither group, nor field, has thought of before. In order for the partnership to be successful though, each side has to appreciate the other's strengths and weaknesses. We've found that constant communication, and clear explanations of background information and the goals of each stage of the project, have been the greatest assets in our relationships with such collaborators.

The interdisciplinary nature of our studies is valuable not only for its immediate benefits to our research, but also for keeping the door open to diverse career paths in the sciences. It's the perfect introduction to the team-based approach common in the industry, a career direction that many students at university eventually take. Not only does it give one the knowledge and the vocabulary to understand other disciplines, but it also provides the necessary communication skills. With the recent introduction of interdisciplinary training programs, such as the Simon Fraser University-University of British Columbia joint bioinformatics graduate training program, and the increase in team-based and problem-based learning approaches, we are hopeful that today's crop of budding scientists will emerge from their training with an appreciation for a variety of disciplines and the ability to move among them effectively. It might not be long, in fact, before we see the lines between different fields start to blur even further than they have already.

Without the cooperation of researchers in several different fields, many of today's important discoveries wouldn't have been possible. Where would the Human Genome Project be without the help of the computer scientists and bioinformaticists whose programs have helped to organize and annotate all that information? Scientists are getting together, talking, and sharing ideas and the results are fascinating. We're finally seeing the elephant, and much more, in our world.