"Currently, biology is a lot of trial and error," Yener said. "With a mathematical model of something like cancerous tissue, you can computationally represent the relationships between cells. That model can then be predictive and eliminate time and energy lost in trial and error."
To non-scientists, interactions between two different types of scientists seems like the norm. But, there are no two groups of scientists more disparate than biologists and computer scientists, according to both Yener and Plopper. For biologists, discovery is in the details. How many genes are being expressed in a tissue? What protein is involved in the disease? Computer scientists seek to represent the larger relationship between different data points. What those data points actually represent is largely irrelevant.
"We have a very unique relationship," Plopper said. "I think it will take my whole career to get people in both fields who currently don't talk to even accept the fact that they should. But if all scientists understand how to generate and use numeric data of some sort, that would really lower the barriers between fields."
Plopper has even created a class, "Cell-Extracellular Matrix Interactions," to develop a new type of data-savvy biologist.
"These discoveries have to come from both fields," Yener said. "Scientists need to trust computational methodologies and that trust will only come when we go back to the basic biology that can be fed into the modeling and tested."
|Contact: Gabrielle DeMarco|
Rensselaer Polytechnic Institute