Single-Cell Proteomic Data for Estimating Influenza Infection Timing

Data from a controlled human challenge with influenza A/California/2009 (H1N1) used to develop immune-based predictive models. The dataset includes longitudinal profiles of major immune cell subsets across multiple time points before and after viral challenge, collected using 42-marker mass cytometry panels. The models were independently validated using data from a separate controlled human influenza challenge study.

Use Cases

• Training machine learning models to estimate days post-infection challenge based on immune profiles.
• Distinguishing virus shedders from non-shedders using single-cell immune population dynamics.
• Validating immune-based predictive models of infection timing in independent challenge cohorts.
• Analyzing the temporal structure encoded in immune cell subset dynamics following influenza infection.

Strengths

• Data originates from a controlled human challenge study, providing a controlled experimental context.
• Includes longitudinal profiling across multiple time points before and after viral challenge.
• Models were independently validated using a separate controlled challenge study.
• 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 98.9 KB, indicating a limited scope and likely small sample size.

Provenance

Source

figshare

Collection Method

Data collected from a controlled human influenza challenge study using mass cytometry.

Freshness

Last updated 2026-03-19 08:43:38; freshness should be verified.