Dr. Guido Sanguinetti
My interests focus on probabilistic modelling of biological systems, with particular emphasis on inference in dynamical systems. I am particularly interesting in using ideas from stochastic processes and machine learning to reconstruct the dynamics of gene regulatory networks and metabolic networks, with applications ranging from understanding pathogenicity in bacteria to design synthetic organisms capable of performing specific tasks (e.g. synthesizing fuels).
Example project: Data-driven identification of biological circuits in gene regulatory networks. Real biological networks exhibit a rich modular structure, where specific subnetworks (called motifs) perform specific functions similar to those played by circuits within complex systems (e.g. low pass filter, amplifier, etc). Can we incorporate this global knowledge into gene regulatory network reconstruction algorithms? See Guido Sanguinetti's research pages for more information.