Integrative Biology Laboratory, Salk Institute for Biological Studies and UCSD
- October 30, 2017
- 2:00 PM
- ECS 241
Many biological systems can be viewed as algorithms designed by evolution to solve computational problems. I will present two such examples. First, I will describe how the olfactory circuit in the fruit fly brain solves the similarity search (nearest-neighbors) problem using a novel variant of a traditional computer science algorithm, called locality-sensitive hashing. Second, I will describe how plant architectures trade-off between common network design principles — minimizing nutrient transport distances and minimizing costs in building infrastructure — using the theory of Pareto optimality. Discovering the strategies biological systems use to solve these problems can lead to new algorithms and new experimental hypotheses. This is joint work with Adam Conn, Joanne Chory, Sanjoy Dasgupta, Ullas Pedmale, and Chuck Stevens.