The Biologically Inspired Neural & Dynamical Systems Laboratory aims to apply techniques developed in computer science to problems in biology and to turn insights gained from biological systems to construct better computational algorithms. A specific goal is to employ computational techniques from machine learning, such as clustering and Bayesian network modeling, to solve problems in functional genomics. Another goal of the lab is to build mathematical models of neural circuitries in the brain.