Klodiana Rizzo Nervo published a dataset from a controlled human influenza challenge study. The data likely contains mass cytometry profiles from immune cells to train random forest models for estimating days post-infection. It was last updated on March 19, 2026.
Use Cases
- Training predictive models to distinguish virus shedders from non-shedders based on immune profiles.
- Estimating days post-infection challenge (DPC) using single-cell immune population dynamics.
- Validating immune-based temporal biomarkers for influenza infection in independent challenge cohorts.
- Analyzing host immune response dynamics following influenza A/California/2009 (H1N1) exposure.
Strengths
- Data originates from a controlled human challenge study, providing a structured experimental context.
- Models were independently validated using data from a separate controlled challenge study.
- The dataset is openly available under a CC-BY-4.0 license.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
- The dataset is 194.6 KB, indicating a limited scope.
Provenance
- Source
- figshare
- Collection Method
- Data collected from a controlled human challenge with influenza A/California/2009 (H1N1) using 42-marker mass cytometry panels.
- Freshness
- Last updated 2026-03-19 08:43:38