Bigger Biology Tackled Through Keyboards Solving crucial biological problems these days can involve trying to figure out huge arrays of individual activities on vastly different scales and timelines, from the rapid genetic mutations of certain viruses to the long-term impact of species extinctions on global ecological processes. Fortunately, a relatively new field of science known as computational biology is coming of age, according to a review paper in the Jan. 17 issue of the weekly journal Science by researchers from the University of California, Davis, and other universities. Dynamic models are an essential tool for understanding complex biological systems. Written by four of the most noted scientists in the field, the paper reviews the role of powerful computational tools in studying ecology, genetics and evolution, infectious diseases, and immunology and virology.
Computational biology is at that point, the authors agree.
Dazzling new high-speed computational technology, enormous and growing sets of data, and more sophisticated approaches to problem solving are now converging. For example, the evolution of altruism has long intrigued biologists. Why would an organism intent on spreading its genes on to the next generation risk anything by helping another organism. Well, computational work has revealed that individuals are more likely to help neighbors than random strangers they expect never to see again and that this can help explain how altruism has evolved. Computational biologists begin to understand these kinds of problems by building a mathematical model.