The Zeller team develops analysis strategies and tools to investigate how the microbiome contributes to human health, disease progression and treatment success, and how it is shaped by host factors such as nutrition and drug intake. The human microbiome, the complex ecosystem of microorganisms colonising our body, has increasingly been recognised as an important determinant of human physiology. Detailed investigations of microbes in situ without culturing have become possible through advances in sequencing technology and computational analysis methodology. These have now started to be applied in large clinical studies to associate changes in microbiome composition and function with human diseases. However, analysis and interpretation of such data remains challenging:.
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The field of protein structure prediction has greatly advanced in recent years thanks to increasingly accurate deep-learning methods. More than protein structures have been predicted in this way and are now available in Pfam, with more to follow. And by exploring these protein structures, they can also start to gradually understand the protein functions. It uses the large, multiple sequence alignments available in Pfam and applies a deep learning model to predict the transformations and structure parameters for each protein. It then applies the Rosetta pipeline to predict the structure.