Putting computational models of immunity to the test—An invited challenge to predict B.pertussis vaccination responses is a research paper published in PLoS Computational Biology (2025). On theSindex it has a DataRank of 0. It has been cited 1 time.
Scored on demand from live citation data
DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
We only score data papers we can read in full — never from an abstract alone.
National Institute of Allergy and Infectious Diseases
Grant: U01AI150753,
National Institutes of Health
Grant: U01AI141995
National Institutes of Health
Grant: U19AI142742
National Institute of Health
Grant: U01AI187062
NIAID NIH HHS
Grant: U01 AI150753
NIAID NIH HHS
Grant: UM1 AI068635
National Institutes of Health
Grant: 5U19AI142742-03
Functional and dysfunctional human CD4 T cell and B cell responses to bacteria and viruses
National Institutes of Health
Grant: 1U01AI150753-01
Developing computational models to predict the immune response to B. pertussis booster vaccination
National Institutes of Health
Grant: 5U01AI141995-05
Identifying mechanisms and correlates of long-lasting vaccine-induced immunity to whooping cough
National Institutes of Health
Grant: 1U01AI187062-01
Towards a predictive understanding of influenza immunity through experimental data integration, iterative model development, and rigorous assessment of model quality
FWCI
0.41
Citation Percentile
0.6%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals