IDeA Networks of Biomedical Research Excellence (INBRE)
12th Annual Tribal College Research Symposium
The Twelvth Annual Tribal College Research Symposium will be hosted by United Tribes Technical College, April 22-23, 2026, at the North Dakota Heritage Center and State Museum in Bismarck in Bismarck, ND. This symposium will include a poster session featuring student research, a keynote address, and breakout sessions. The symposium will begin with a poster session and reception Wednesday evening, followed by the Keynote Address and Breakout Sessions on Thursday. Registration is free. Deadline April 1, 2026. Registration and more information here.
Virtual Indigenous Data Science (VIDS) Academy
The Virtual Indigenous Data Science Academy is a program hosted by the UND School of Medicine and Health Sciences in partnership with area Tribal colleges to begin to address the growing demand for data science education. This training academy (July 20 To July 31) will introduce students to the foundations of data science and analytics. The Virtual Indigenous Data Science Program introduces students to data, computational approaches, access to resources, and career opportunities in data science, and address the under-representation of American Indians and Alaskan Natives in the biomedical research workforce.
The Initiative builds on the NIH-funded ND INBRE Health & the Environment program, which is housed at the UND School of Medicine and Health Sciences.
The deadline to register for the 2026 Virtual Indigenous Data Science Academy is March 31, 2026.
Free Access to Cloud-Based Data Integration Platform
Through a collaboration of the National Institute of General Medical Sciences (NIGMS), Google-GCP, Amazon-AWS, and the NIH’s Institutional Development Awards (IDeA) states making use of its IDeA Networks of Biomedical Research Excellence (INBRE) program, a multi-disciplinary team of scientists has developed the NIGMS Sandbox Modules, a set of interactive GitHub repositories and videos that enable self-learning and use of any researcher’s own data.
Leveraging the scalability and computational power of Google Cloud, the platform allows users to seamlessly integrate diverse omics datasets, including genomics, transcriptomics, proteomics, and metabolomics. The tool facilitates the exploration of large datasets, running complex analyses without requiring local infrastructure.
This tool is designed to enhance both classroom learning and cutting-edge research, providing an accessib le and efficient environment for bioinformaticians, researchers, and students to engage with multi-omics data.
More information about Cloud-Based Data Platform.