GOOD 2025

At IFOM, bridging the gap between wet-lab scientists and complex computational infrastructures is a priority. Many biologists find command-line tools and HPC systems challenging to use. To address this, we introduced Open OnDemand (OOD) as a user-friendly portal, streamlining access to our computational resources and enabling a more inclusive, collaborative workflow.
Our OOD provides a graphical interface allowing even novice users to run advanced bioinformatics analyses. Central to this effort is the integration of nf-core (Nextflow) pipelines—commonly employed for scalable, reproducible research—directly into OOD. As a result, biomedical researchers can effortlessly execute and manage complex workflows without any deep computational expertise. Indeed, dynamic web forms let users run complex bioinformatics pipelines such as those privide by the nf-core community (https://nf-co.re/pipelines), RNA-seq is one example.
Departing from the standard OOD guidelines, we have implemented a distinctive conda environment management solution wrapped within Apptainer containers. This approach ensures reproducible software stacks while simplifying environment selection and customization. Combined with Jupyter notebooks served through OOD, researchers can interactively explore data, prototype analyses, and visualize results. The seamless availability of these containerized environments breaks down traditional barriers, fostering a more iterative and data-driven scientific process. This is a great example of integration between software user friendliness and compliance with best practices for scientific reproducibility.
To further support users, we have integrated widely used imaging applications such as Fiji and QuPath into OOD. Wet-lab researchers can now perform image analysis, data inspection, and computational tasks within a unified platform, minimizing the friction that often separates bench work from in silico exploration eliminating the tricky proliferation of standalone ad-hoc workstations linked to specific scientific instruments.
In summary, OOD at IFOM demonstrates how a thoughtfully designed computational gateway can democratize access to powerful data analysis resources,closing the gap between experimental biology and computational infrastructure, promoting research efficiency. We believe that Open OnDemand is a robust solution to improve reproducibility and a stronger culture of collaboration between biomedical researchers and computational scientists.