Complex Systems Made Simple
February 19, 2013
Just as the name implies, complex systems are difficult to tease apart. An organism’s genome, a biochemical reaction, or even a social network all contain many interdependent components—and changing any one of them can have pervasive effects on all the others. In the case of a very large system, like the human genome, which contains 20,000 interconnected genes, it’s impossible to monitor the whole system at once.
But that may not matter anymore. In a paper published in the prestigious multidisciplinary journal Proceedings of the National Academy of Science, Northeastern network scientists have developed an algorithm capable of identifying the subset of components—or nodes—that are necessary to reveal a complex system’s overall nature.
The approach takes advantage of the interdependent nature of complexity to devise a method for observing systems that are otherwise beyond quantitative scrutiny.
“Connectedness is the essence of complex systems,” said Albert-László Barabási, one of the paper’s authors and a Distinguished Professor of Physics with joint appointments in biology and the College of Computer and Information Science. “Thanks to the links between components, information is distributed throughout a network. Hence I do not need to monitor everyone to have a full sense of what the system does.”