I’d like to remind the NIGMS community of our clearinghouse site of materials designed to teach rigorous experimental design and enhance data reproducibility. There, you’ll find links to a number of online resources including:
- NIH-developed modules on integral aspects of rigor and reproducibility in the research endeavor, such as bias, blinding, an exclusion criteria
- The Big Data to Knowledge program’s virtual lecture series on the data science underlying modern biomedical research
- A 6-week iBiology course designed for students and practitioners of experimental biology
- Rigor and reproducibility training modules from the Society for Neuroscience
- Grantee-developed courses on topics such as experimental design and analysis, controls in animal studies, computational tools for reproducible science, and more
I encourage you to visit this page and share the featured resources with your colleagues and trainees so that they are aware how crucial it is that the results of NIH-supported biomedical research are reproducible, unbiased, and properly validated. You may also want to review NIH’s Rigor and Reproducibility web portal for additional guidelines, instructions, and resources.