NIAID funded projects are generating large, diverse, complex data sets, and our research communities have become a data-intense enterprise. There is a critical need to transform these data into knowledge to more fully understand pathogen transmission and evolution, pathogen-host interactions, host immune response, and infectious and immune-mediated disease pathogenesis, as well as to develop new and improved diagnostics, therapeutics, and vaccines. Hence the need for findable, accessible, interoperable, and reusable (FAIR) data and software that are innovative and sustainable. NIAID also encourages repositories to follow the TRUST Principles (Transparency, Responsibility, User focus, Sustainability, and Technology).
NIAID is addressing this need through the Office of Data Science and Emerging Technologies (ODSET). The office will build partnerships across NIAID to harness the power of data by coordinating NIAID’s data science portfolio and lead the planning and execution of trans-NIAID data science research programs, activities, and related initiatives both intramurally and extramurally. In addition, the office will provide guidance on data-management and -sharing practices to ensure NIAID’s research adheres to NIH policies to serve knowledge sharing, secondary use, and reproducibility of NIAID-funded research data as well as enable opportunities to develop a data science workforce.
NIAID Now Blog
Resources for Researchers
- 3D Reconstruction via Stereoscopy for the Study of Mosquito Swarms - tool for visualization of swarms
- AccessClinicalData@NIAID – tool to access data sets from NIAID COVID-19 clinical trials and other sponsored clinical trials
- Bioinformatics Resource Center for Infectious Diseases - resource for bacterial, eukaryotic, fungal, viral, and other vectors of human pathogens
- Center for International Blood and Marrow Transplantation Research (CIBMTR) Database - data on outcomes of blood and bone marrow transplant procedures
- ChemDB HIV - opportunistic infection and tuberculosis therapeutics database
- RFA-AI-21-035, Exploratory Data Science Methods and Algorithm Development in Infectious and Immune-Mediated Diseases (R21, Clinical Trial Not Allowed)
- RFA-AI-21-020, Early-Stage Development of Data Science Technologies for Infectious and Immune-Mediated Diseases (U01, Clinical Trial Not Allowed)
- RFA-AI-21-021, Enhancement or Sustainment of Data Science Tools for Infectious and Immune-Mediated Diseases (U24, Clinical Trial Not Allowed)
- NOT-AI-21-011 Secondary Analysis of Existing Datasets for Advancing Immune-mediated and Infectious Disease Research (Notice of Special Interest (NOSI)
- PAR-19-229 Informatics Methodology and Secondary Analyses for Immunology Data in ImmPort (UH2 Clinical Trial Not Allowed)
- PAR-20-089 Biomedical Data Repository (U24 Clinical Trials Not Allowed)
- PAR-20-097 Biomedical Knowledgebase (U24 Clinical Trials Not Allowed)
NIAID Emerging Leaders in Data Sciences Fellowship Program
This fellowship program aims to establish a cadre of talented data scientists (i.e., expertise in bioinformatics, computational biology, epidemiology, computer science, engineering, or applied mathematics) with a keen interest in applying their knowledge and skills to advance NIAID’s research mission.