Current Reserach: Emergent Behaviors in M. xanthus
A flock of birds, containing thousands of individuals flying at high speeds, is able to execute complex behaviors and patterns at the scale of the flock. This seemingly simple behavior baffled scientists until recently. Explanations such as thought-transference (Selous 1931), electromagnetic communication (Heppner 1974), and chorus-line like maneuvers (Potts 1984) were proposed. However a much simpler explanation was found when the maneuvers of individual birds were modeled (Reynolds 1987). Reynold's modeling showed that behaviors of a flock of birds can emerge from three simple rules: 1) avoid crowding out your neighbors, 2) steer towards the average heading of your neighbors, and 3) steer towards the average position of your neighbors. Like many other complex behaviors and patterns in nature, a flock of birds does not need a leader or even high order thought processing. These behaviors instead emerge from chaotic systems following simple rules.
To understand how order can emerge from chaotic systems, the interactions between individuals must be determined using scientific observation and hypothesis testing. These interactions are then used to create computational models that simulate the behaviors of the individual members based on the rules of interaction. Computational models allow for the study of behaviors that are not apparent by studying the individual, a hallmark property of emergent complexity. Many important systems such as the interactions between stem cells to create organs, or between neurons to create thought processes have complex and vast interactions that currently can not be modeled in full. To begin to understand how nature has utilized the properties of emergent complexity, model systems must be developed. I study Myxoccous xanthus as a model system for emerget complexity by trying to undestand the cell-to-cell interactions that lead to rippling and development.
Myxococcus Xanthus Cell Rippling:
Myxococcus Xanthus During Development:
- BS in Bioinformatics, Rochester Institute of Technology