As AI research continue to accelerate, many Statistics and biostatistics faculty members are eager to explore new more data-intensive research directions. Recently, a new resource for the statistics and biostatistics community was launched: A comprehensive biomedical data resource guide, available at here. This platform serves as a curated collection of links to diverse biomedical datasets, enabling researchers and educators to access a wide variety of data types for innovative statistical research and teaching.

Currently, the platform provides links to resources for eight different data types:

  • Electronic Health Records (EHR) Data
  • Genomics Data
  • Imaging Data
  • Microbiome & Metagenomics Data
  • Clinical Trial Data
  • Biobank Data
  • Spatial Transcriptomics Data
  • Proteomics Data

These links direct users to external datasets and repositories, offering an extensive starting point for exploring advanced statistical methods and applications in diverse biomedical fields. In addition, we are preparing a series of follow-up papers that will detail these data types and their associated major scientific questions. These papers aim to provide insights into the statistical challenges and opportunities posed by each data type, fostering collaboration and innovation in statistical and biomedical research. Please encourage your colleagues to explore this platform and consider leveraging these resources for research projects, collaborations, or coursework.

Please reach out to Hongtu Zhu (UNC–Chapel Hill) for feedbacks and suggestions.