The NIAID Office of Data Science and Emerging Technologies (ODSET) highlights publications that feature innovative uses of data science and bioinformatics in infectious, immune-mediated and allergic disease research.
Explore NIAID data science publications on PubMed:
- NIAID-funded publications that use data science or computational biology (since 2023).
- Publications funded or co-funded by ODSET.
- Publications from the Harnessing Big Data to Halt HIV initiative.
If you would like to feature a publication on this page, please contact datascience@niaid.nih.gov. Publications should feature research related to infectious, immunologic, and allergic diseases; include data science or a related discipline; and cite NIAID funding in the manuscript. Please include in your email:
- The title of your published article.
- A link to the article.
- A 50-60 word description of the article.
55 Results
Tracking B cell responses to the SARS-CoV-2 mRNA-1273 vaccine
July 25, 2023 Cell Reports
Using multiomic single-cell analyses, the authors show a coordinated trajectory involving plasmablasts and activated and resting memory B cells in response to primary SARS-CoV-2 mRNA vaccination. Spike-specific BCR repertoire analysis shows incremental affinity maturation across the 6-month study period and reveals evidence of convergence among study participants and other cohorts.
Co-expression of Foxp3 and Helios facilitates the identification of human T regulatory cells in health and disease
June 7, 2023 Frontiers in Immunology
In vivo studies in humanized mice and in patients demonstrate that Foxp3 expression is not upregulated in human CD4+ T conventional cells when activated under a variety of inflammatory conditions. Thus, Foxp3 expression alone can be used as a marker for bona fide T regulatory cells in vivo. The combination of Foxp3 and Helios should be mandatory for quantification of Treg that have been expanded in vitro for use in cellular biotherapy or for production of CAR-Treg.
Variable Selection for High-Dimensional Nodal Attributes in Social Networks with Degree Heterogeneity
April 13, 2023 Journal of the American Statistical Association
Researchers considered a class of network models, in which the connection probability depends on ultrahigh-dimensional nodal covariates (homophily) and node-specific popularity (degree heterogeneity). A Bayesian method is proposed to select nodal features in both dense and sparse networks under a mild assumption on popularity parameters. The proposed approach is implemented via Gibbs sampling.
Developing a standardized but extendable framework to increase the findability of infectious disease datasets
February 23, 2023 Scientific Data
Biomedical datasets are increasing in size, stored in many repositories, and face challenges in FAIRness (findability, accessibility, interoperability, reusability). To improve FAIRness of their datasets and computational tools, authors representing infectious disease researchers from 15 centers evaluated metadata standards across established biomedical data repositories, created a reusable metadata schema based on Schema.org and catalogued nearly 400 datasets and computational tools.
The Immune Signatures data resource, a compendium of systems vaccinology datasets
October 20, 2022 Nature
The NIH/NIAID Human Immunology Project Consortium (HIPC) has leveraged systems immunology approaches to identify molecular signatures associated with the immunogenicity of many vaccines. To support comparative analyses across different vaccines, the authors created the Immune Signatures Data Resource, a compendium of standardized systems vaccinology datasets.