Students and researchers! Apply for free access to cloud-based data integration platform via UND
Principal investigator Dr. Sandeep Singhal, an associate professor in UND’s Department of Pathology, is leading UND’s efforts on this a multi-institutional National Institute of General Medical Sciences (NIGMS) project designed to help students, researchers, and clinicians leverage artificial intelligence (AI) and cloud computing to benefit students and researchers.
With research becoming increasingly data-driven, biomedical researchers need access to big data and bigger analytical capacity. Unfortunately, not all institutions have access to high performance computing (HPC) on-site. Today, however, cloud computing can provide this access broadly, alleviating the need for high performance computing at each institution.
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.
Key features include interactive data visualization, advanced statistical analysis, and secure data storage.
This tool is designed to enhance both classroom learning and cutting-edge research, providing an accessible and efficient environment for bioinformaticians, researchers, and students to engage with multi-omics data. The goal of this lowering-of-barriers to big omics data research is an increase in the likelihood of more and better treatments for more health conditions.
To learn more about how you can use this cloud-based platform for your own big “omics” research or teaching needs, read this Integrating Multi-Omics Datasets primer. And for more information on how to start your own big data bioinformatics project, contact Dr. Singhal to access these cost-free resources.
This research was supported by the National Institute of General Medical Sciences of the National Institutes of Health under Award Number P20GM103442.
