Game Theory and Bacteria
https://www.sciencedaily.com/releases/2019/10/191009093948.htm
This article describes how a group of researchers at Washington State University are developing a unique application for graph theory: identifying antibiotic resistant genes in bacteria. The two researchers, one from the School of Electrical Engineering and Computer Science and the other from the School of Global Animal Health, combined their distinct backgrounds to develop this process. Using game theory and machine learning they were able to detect the presence of previously unrecognized antibiotic-resistant genes in bacteria with an accuracy of 93 to 99 percent. With the growing prevalence of antibiotic-resistant bacteria in recent years, this development is especially crucial as more resistant strains of bacterial infections are discovered leading to an increase in diseases and a decrease in the effectiveness of some drugs.
Since the application of game theory is most common in economic, psychology, etc. it was fascinating to see an application in biology that completely lacked the “human” element that usually determines the logic of the game. In this application, rather than modeling the behavior between people they are modeling how the several features of genetic material, such as it structure and physiochemical properties, interact. According to Broschat, one of the researchers, “This novel game theory approach is especially powerful because features are chosen on the basis of how well they work together as a whole to identify likely antimicrobial-resistance genes — taking into account both the relevance and interdependency of features.” The ideas referenced in this quote connect to some of the topics we covered in class such as the idea of cooperation and interdependence between players (or in this case genetic material) and how this affects the outcome.