Flywheel Case Studies Enabling Scientific Collaboration at UCI Yassa Lab

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	Enabling Scientific Collaboration at UCI Yassa Lab Flywheel

Enabling Scientific Collaboration at UCI Yassa Lab

Flywheel

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
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. Read More
About 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. Read More
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. Read More Log in to view content
Contents

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

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.

About 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.

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.

Impact #1	The Flywheel system allowed data to be pushed directly from their MRI scanner through Flywheel's DICOM connector.
Impact #2	Remote users could easily transfer data to the project via command line tools or a drag and drop web uploader.
Impact #3	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.

Impact #1

The Flywheel system allowed data to be pushed directly from their MRI scanner through Flywheel's DICOM connector.

Impact #2

Remote users could easily transfer data to the project via command line tools or a drag and drop web uploader.

Impact #3

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.

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Overview

Enabling Scientific Collaboration at UCI Yassa Lab

Operational Impact