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.
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Pfam releases structures for every protein family
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Creative and original research recognised by German association of microbiologists. The VAAM represents around 3, microbiologists from academia and industry. The spectrum of their research ranges from bacteria, archaea, and fungi in food and water to pathogens, genome analyses, and industrial use of microorganisms and their enzymes. His research focuses on bacterial genomes. His research group develops high-throughput genetic and biochemical methods that give insights into bacterial mechanisms and interactions.