Enabling Scientific Collaboration at UCI Yassa Lab
Company Size
1,000+
Region
- America
Country
- United States
Product
- Flywheel research data management platform
- Flywheel's DICOM connector
- Flywheel gears
Tech Stack
- Google Cloud Platform
- MATLAB
- Python
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Digital Expertise
- Innovation Output
- Productivity Improvements
Technology Category
- Infrastructure as a Service (IaaS) - Cloud Computing
- Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries
- Education
- Healthcare & Hospitals
Applicable Functions
- Product Research & Development
- Quality Assurance
Use Cases
- Remote Collaboration
Services
- Cloud Planning, Design & Implementation Services
- Data Science Services
- System Integration
About The Customer
The customer in this case study is the Yassa Lab at the University of California, Irvine (UCI). The lab is led by Dr. Michael Yassa, Ph.D., Director of the Translational Neurobiology Lab. The Yassa Lab studies changes in memory over a lifetime, methods for diagnosing progressive brain diseases and mood disorders, and paths to treatment. The lab is involved in a multicenter collaboration studying biomarkers of Alzheimer's disease in Down syndrome. The study investigates whether immunological factors active in Down syndrome are also involved in Alzheimer's Disease. The lab routinely collects and analyzes large, complex imaging data from a variety of MRI systems, including Siemens, Philips, and Bruker scanners.
The Challenge
The Yassa Lab at the University of California, Irvine (UCI), led by Dr. Michael Yassa, was facing several challenges. They were struggling with managing multi-center collaboration involving the collection of large data sets, quality control, analysis, and submission to NIH databases. The growing data and analytic complexity were impeding data reuse and scientific reproducibility. They were also looking for ways to best support and collaborate with other labs in the UC Irvine community. The lab was involved in a multicenter collaboration studying biomarkers of Alzheimer's disease in Down syndrome, which required secure sharing and processing of a variety of data.
The Solution
The Yassa Lab adopted the Flywheel research data management platform to streamline collaboration and core operations. The platform was deployed on Google Cloud Platform to simplify data transfer from collaborators and automate and document computational processing. The Flywheel system allowed data to be pushed directly from their MRI scanner through Flywheel's DICOM connector. Remote users could easily transfer data to the project via command line tools or a drag and drop web uploader. Once data landed in the system, rules controlled automated conversion from DICOM to NIFTI format using Dcm2Niix, execution of quality control algorithms, such as MRIQC, and analytic applications such as Freesurfer and fMRIPrep. All data and analytic results were available to project members via a secure web browser interface with access controls.
Operational Impact
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