Teams

GenX implements Confidential Computing technologies for privacy-preserving multi-party genomic and medical data analysis.

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The overarching theme of the research in our group is the understanding of the information encoded in genomic sequences, and how this information is processed in the pathway leading from DNA to protein sequences. We are intrigued by the parallelism between computation and the processing of information encoded in biological sequences. The bulk of ouf research currently focuses on the mechanisms underlying RNA production (transcription) and post-processing (splicing), and it is increasingly ...

Department of Molecular NeuroscienceCenter for Brain ResearchMedical University of Vienna

Dev team for Hecatomb

In view of the complexity in modeling phylogenetic network experiments, the present work introduces a workflow for phylogenetic network analyses coupled to be executed in High-Performance Computing (HPC) environments. The workflow aims to integrate well-established software, pipelines and scripts, implementing a challenging task since these tools do not consistently profit from the HPC environment, leading to an increase in the expected makespan and idle computing resources.

The Hurwitz Lab was established in August, 2014 at the University of Arizona in the Department of Biosystems Engineering. Our lab focuses on large-scale –omics datasets, high-throughput computing, and big data analytics. We leverage these technologies to answer questions related to the relationship between microbes, their hosts, and the environment.