Fast biological network reconstruction from high-dimensional time-course perturbation data using sparse multivariate Gaussian processes

Time-course data observed under the perturbation of biological systems contain rich information about the salient structure of interconnectivity among the entities of the network underlying the system. Challenges: few noisy high-dimensional measurements at
non-uniformly–spaced intervals; missing data; and computational complexity of inference, parameter estimation, and sparse structure search.