multiMarker

multiMarker models relationships between metabolomic biomarkers and food quantity data to quantify and predict dietary intake from multiple biomarkers.

Key Features:

• Inference of relationships: Infers relationships between two or more metabolomic biomarkers and specific food intake measurements.
• Prediction from biomarker data: Predicts food intake quantities using available biomarker data alone.
• Quantification of uncertainty: Produces distributions of predicted intakes rather than single-point estimates to represent prediction uncertainty.

Scientific Applications:

• Nutrition biomarker research: Enables continuous and objective quantification of food intake using metabolomic biomarkers.
• Epidemiological studies and clinical trials: Supports dietary exposure assessment in epidemiology and intervention studies.
• Diet–disease and personalized nutrition research: Facilitates investigation of diet–disease relationships and biomarker-based approaches for personalized nutrition.

Methodology:

Integration of metabolomic data with statistical modeling techniques to model relationships between multiple biomarkers and food intake, predict intake from biomarkers, and generate distributions of predicted intakes.