AD Workbench Workspaces
Collaborative, secure environments for teams to work on their research projects. They can be deployed in various hubs across different geographic regions to meet governance and compliance standards, including GDPR and HIPAA.
AD Workbench Workspaces come pre-equipped with tools commonly used by bioinformatics scientists, such as R, Python, and bioinformatics/imaging software. Additionally, workspace users have access to infrastructure support, including virtual machines and storage accounts.
Users can upload their own data, bring in custom tools, and configure the workspace to fit their research needs. Workspace Administrator oversees the export of results while restricting data downloads, ensuring security. A detailed audit trail is also maintained for added security.
Enabling Collaboration
Workspaces are private to their members, and user access can be granted and maintained by a Workspace Administrator.
Once files and data are uploaded to your Workspace, team members can access them via RStudio, Jupyter, and virtual machines.
Cloud-Based and Customizable
Cloud-based workspaces are located in regions to comply with geography-based data sharing policies and laws.
Each Workspace is configured based on file and database storage and computing requirements, virtual machine requirements, and any additional add-on services (such as the R Shiny server).
Every Workspace includes a broad selection of the most popular R and Python packages. Users can also upload their favorite tools and preprocessing pipelines to workspaces to analyze clinical, neuroimaging, and omics data made accessible via AD Workbench.
AD Curation Studio
Users have access to the AD Curation Studio, a suite of tools designed to help researchers prepare, anonymize, and harmonize data from international clinical trials and biomedical and health research before making it discoverable via the AD Workbench.
Let’s Get Started!
Once you create a Workspace and set up your environment, including which R and Python packages you want to use, you can invite members of your team, request datasets from FAIR, and get to work!
Start Collaborating on Research Projects Now!
Examples of how researchers use Workspaces
- Exploring Alzheimer's Disease Heterogeneity: Researchers investigate the heterogeneity of Alzheimer’s, particularly through factors like amyloid composition and differential protein expression across brain regions.
- Testing Diagnostic and Predictive Models: Workspaces are created to develop models that may improve Alzheimer’s diagnostics, assess model performance, and create explainable AI models.
- Studying Environmental and Demographic Factors: Projects focus on understanding Alzheimer’s prevalence in underrepresented populations and studying the influence of environmental conditions.
- Omics Data Analysis: A common goal is to analyze omics data to understand disease mechanisms, identify biomarkers, and assess genetic contributions to Alzheimer’s progression.
- Pilot Testing and Validation: Workspaces are used to test and validate newly generated datasets and tools in preparation for larger-scale studies.
- Preparing Data for Sharing and Analysis: Many researchers create workspaces specifically to pre-process raw data, making it more suitable for downstream analysis and easier to share with the broader ADRD research community.