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Computational Genomics Laboratory

PI: Prof. Francesco Lescai

This laboratory is interested in modelling inflammation as a key predictor of phenotype trajectories. In order to tackle this challenge, we focus our activities on two main areas, tightly integrated with each other:

  • computational genomics methods, to uncover patterns of genomic variation that explain individual differences in the inflammatory response
  • the use of machine/deep learning to identify genomic and non-genomic parameters to predict an individual’s inflammatory response and how in turn this will affect the evolution of a phenotype or disease.