Systems approach to gene regulation biology through nuclear receptors
The Lawrence group is working on developing methods of evalutating biological "omics" data by systematic data-driven model building, model validation, and analysis, with the ultimate goal of providing software that can reveal biological insights from the highly complex data sets. It aims to produce standardized software tools that are powerful, easy-to-use, and reliable.
Prof. Lawrence is an expert on integration of mechanistic models, based around differential equations, with probabilistic approaches to allow for a rigorous Bayesian analysis of a biological system. These approaches are particularly appropriate for computational systems biology where the data is typically sampled more sparsely and with higher noise than in traditional engineering systems. His background is in statistical machine learning, and his expertise extends to latent variable modelling including non-linear probabilistic latent variable models.
