Client success story
Bioinformatics Analysis Platform
Business Value: Retention and Resource Optimization of Bioinformaticists and Scientists
Summary: Improve Informatics Analysis and Delivery
A contract research organization needed a way to organize their informatics analysis activities to improve the quality of results delivery and improve staff productivity. bPrescient delivered a platform that supported self-service analytics executed on high performance compute infrastructure and allowed the company’s team to focus on new development.
Challenge: Optimize the Bioinformatics Team For High-Level Work
The bioinformatics team needed to perform a wide array of analyses but spent more of their time helping users run analyses, manage workflows, and share results than they did developing new tools. This impacted the organization’s ability to develop new analytical pipelines, increased the time to complete projects, affected the quality of results, and caused employee burnout.
Solution: bPrescient Experts Build Application and Implement Informatics Database
bPrescient’s development team worked closely with the client’s bioinformatics team to implement a robust and modular workflow framework with a supporting database that manages and organizes their informatics pipelines and results. The system supports advanced microbial and proteomic analyses and assay design and allows users to run analysis workflows and manage their results using a simple web user interface. bPrescient was responsible for the design, full-stack development, and testing of the application, in addition to the system enhancements which provided customer-facing analytic results.
Outcome: New Self-Service Bioinformatics Analysis Platform
The client’s scientists now run most of their own analyses without help from the bioinformatics team. This frees them up to concentrate on developing new applications to meet the needs of their customers and to pursue innovative new methods. The quality of the results is improved because the analytics pipelines are being run in a standardized and reproducible way. In addition, new scientists can be onboarded more quickly and sharing of results within the platform leads to improved collaboration. Ultimately, the system reduces costs, shortens timelines for project execution, and allows increased innovation by the bioinformatics team.
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