The rapid growth of high-throughput technologies has transformed biomedical research.
With the increasing amount and complexity of data, scalability and reproducibility have …

Highlights•Almost 600 complete plant genome assemblies are now available in public
repositories.•New sequencing technologies are producing genome assemblies of …

Introduction: Artificial intelligence (AI) and machine learning (ML) are increasingly used in
many aspects of drug discovery. Larger data sizes and methods such as Deep Neural …

Deep learning is transforming the analysis of biological images, but applying these models
to large datasets remains challenging. Here we describe the DeepCell Kiosk, cloud-native …

Workflows are among the most commonly used tools in a variety of execution environments.
Many of them target a specific environment; few of them make it possible to execute an …

Background Metabolomics is the comprehensive study of a multitude of small molecules to
gain insight into an organism's metabolism. The research field is dynamic and expanding …

Background: In biomedical imaging research, experimental biologists generate vast
amounts of data that require advanced computational analysis. Breakthroughs in …

As Kubernetes becomes the infrastructure of the cloud-native era, the integration of workflow
systems with Kubernetes is gaining more and more popularity. However, when migrating the …

Background The complex nature of biological data has driven the development of
specialized software tools. Scientific workflow management systems simplify the assembly of …

In this work, we address the problem of running HPC workloads efficiently on Kubernetes
clusters. To do so, we compare the Kubernetes' default scheduler with KubeFlux, a …