The Big Data for Discovery Science Center (BDDS) - comprised of leading experts in biomedical imaging, genetics, proteomics, and computer science - is taking an "-ome to home" approach toward streamlining big data management, aggregation, manipulation, integration, and the modeling of biological systems across spatial and temporal scales.

Brain Morphometric Growth Charts

In this use case, BDDS researchers are working on tracking brain morphometric changes in children. This approach, which is evolving, presents several Big Data challenges where BDDS tools namely Deriva, BDBags, MINIDs and workflow pipelines were extremely helpful.

An MRI-based neuroanatomical morphometric growth chart can be used to evaluate a single subject's neuroanatomy in context of age and gender related norms, similar to a growth chart. We have created a framework where users can upload a T1-weighted image, add age and gender, and receive as an output a report about how that individual compares to age norms for that gender. We constructed a preliminary data catalog using publicly available T1-weighted data from 1654 typically developing children ages 3-20 years.