Modern biomedical research is becoming increasingly quantitative and reliant on computational methods, with growing use of large and complex datasets to address biomedical research questions and advance human health. To help address the need for biomedical researchers with cutting-edge computational and quantitative skills, we have updated the focus areas of our Predoctoral T32 Training Program in Computational Biology, Bioinformatics, and Biomedical Data Science (formerly called Bioinformatics and Computational Biology). In doing this, we aim to better integrate training in data-science approaches throughout the curriculum and during the mentored research period. We are now placing a strong emphasis on programs that:
A current research challenge is harmonizing vast amounts of heterogeneous biological data so that it can be stored, extracted, analyzed, presented and shared in a broad, uniform manner. An important step to overcoming this obstacle is creating data-related standards.
Toward this goal, NIH has issued a request for information (RFI) seeking comments on information resources for data-related standards widely used in biomedical science. Feedback on standards considered most critical, as well as existing relevant resources, could inform plans to develop a publicly available, Web-based information resource on data-related standards.
The deadline for responding to the RFI is September 30, 2014.