Overview
As research teams increasingly rely on computational methods to analyze complex experimental data, many scientists face barriers to independently using bioinformatics tools and modern analytical workflows. A leading federal research institution sought to strengthen internal capability by improving researchers’ access to practical training, standardized workflows, and ongoing computational guidance.
BioTeam partnered with the institution to build sustainable bioinformatics and scientific computing capabilities across research groups. Through structured training programs, hands-on collaboration, and knowledge sharing, BioTeam helped researchers develop the skills needed to perform their own analyses and adopt reproducible research practices.
This approach reduced reliance on external support while enabling broader adoption of modern computational methods, helping the institution scale data-driven research more effectively.
Impact Summary
- Delivered or hosted 25+ training sessions, increasing institutional computational autonomy
- Enabled researchers to independently use high-performance computing and modern analysis tools
- Established standardized, reproducible workflows using GitHub and containerization
- Created long-term institutional capability in bioinformatics and scientific computing
Challenge
While computational methods were becoming essential across research programs, the institution lacked a scalable way to support them. Expertise was fragmented across labs, workflows were inconsistent, and training was ad hoc rather than systematic. Researchers often relied on informal support or external specialists to complete analyses, making it difficult to standardize approaches, ensure reproducibility, or build momentum across teams. Without a cohesive framework for training and workflow development, computational capabilities remained uneven and hard to scale institution-wide.
Services Provided
Structured Training Program
BioTeam delivered structured training programs designed to build both foundational and advanced technical skills. These included one-hour Lunch ‘n’ Learn sessions open to the broader research community, covering topics such as:
- Biowulf high-performance computing
- AI and Machine Learning
- GitHub and version control
- Python and R for scientific computing
- Data analysis using Pandas
- Containerization
- Data management and sharing
- Scientific pipeline development
Specialized hands-on training
In addition to group training, BioTeam provided individualized hands-on training sessions for specific labs and researchers, enabling direct application of computational techniques to their research workflows.
Knowledge transfer and documentation
BioTeam created comprehensive documentation and shared code through GitHub repositories, ensuring that workflows were reproducible, maintainable, and accessible to the research community.
Approach
BioTeam designed an approach focused on empowering the scientists and building computational workflows they could easily maintain over time.
Workforce capability development
BioTeam delivered structured training programs to help researchers develop practical computational skills, enabling them to independently use HPC systems, analyze datasets, and develop reproducible workflows.
Standardization of workflows and infrastructure
BioTeam introduced modern workflow practices to improve consistency and scalability across research teams, including:
- Version-controlled repositories using GitHub
- Containerized pipelines
- Standardized documentation
- Reproducible scientific workflows
Strategic advisory and collaboration
BioTeam provided strategic guidance on data management, pipeline development, and workflow modernization, helping the institution build a scalable and sustainable computational foundation.
Outcomes
BioTeam delivered over 25 training sessions, significantly increasing researchers’ technical autonomy and enabling them to independently perform complex analyses. This training created a multiplier effect, enabling knowledge and technical capabilities to spread across labs and research groups.
By combining training, documentation, and strategic guidance, BioTeam helped establish a sustainable computational ecosystem that will continue to support scientific discovery well beyond the engagement.
