Large-scale high-throughput data is the basis of modern bioinformatics. This data comes in many forms, including, but not limited to: genome sequencing, transcriptomics, proteomics, and metagenomics. The analysis of these types of data requires the use of advanced statistical and computational methods, as well as large-scale data mining, and thus demands a significant amount of computational power. The major projects in this group involve the computationally intensive analysis of large-scale data to understand microorganisms, in particular the development of antibiotic resistance, interactions between bacteria in communities and evolution of pathogenicity. For this, we are analysing data from transcriptomics, proteomics, and metagenomics, as well as performing functional prediction, structure prediction, and comparative genomics. In addition to the analysis of such data, this group also devotes work to software development, particularly the development of new metagenomic data analysis tools.