Friday Lunch Seminar – 15 Feb 2019 - 11:15

Alice McHardy

Machine Learning  in Infection Research

HZI, Forum X 0.13

Biomedical research currently transforms into a data science discipline, due to the increasingly large volumes of different types of omics and medical data that are being generated
and recorded. Accordingly computational methods, are becoming more and more relevant for processing and analysing these data, with machine learning in particular having the potential to move the field forward.
Such methods can generate hypotheses about the underlying key players in infectious processes, in terms of taxa, functions or evolutionary alterations, for instance, or be the basis of data-based predictors for
personalized medicine, e.g. in diagnosis and therapy. I will present some examples of the groups’ recent work in the area, focusing on microbiome-related diseases and microbial pathogens.