Teams

Mass spectrometry imaging, which localizes molecules in a tag-free, spatially-resolved manner, is a powerful tool for the understanding of underlying biochemical mechanisms of biological phenomena. When analyzing MSI data, it is essential to delineate Regions-of-Interest (ROIs) that correspond to tissue areas of different anatomical or pathological labels. Spatial segmentation, obtained by clustering MSI pixels according to their mass spectral similarities, is a popular approach to automate ROI ...

This team is a testing grounds for the DeSci Labs research object development team.

Computational Biology lab at the University of Lausanne, department of computational biology (DBC). Member of the swiss institute of Bioinformatics.We aspire to better understand gene evolution and function, using statistical and computational methods. The key questions underlying our research are:How can we best extrapolate our current knowledge of molecular biology, concentrated in just a handful of model organisms, to the rest of life?Conversely, how can we exploit the wealth and diversity of ...

Workflows created as part of the Earth Biogenome Project Norway

Our team focuses on advancing the field of Dependent Task Scheduling in edge computing environments. We specialize in modeling dependent tasks as Directed Acyclic Graphs (DAGs) to optimize resource allocation and improve overall system performance in edge computing scenarios. Our research encompasses:1. Development of novel scheduling algorithms for DAG-based tasks in edge computing2. Performance analysis and optimization of existing scheduling strategies3. Implementation and evaluation of DAG-based ...

Sequencing facility at the University of Edinburgh

EJPRD WP13 case-studies workflows from phase 1.