CrossLabFit: A novel framework for integrating qualitative and quantitative data across multiple labs for model calibration
Fig 4
Parameter distribution and likelihood profiles for cycle Lotka-Volterra model.
Panel (a) shows violin plots illustrating the variability and density of the estimated parameters a2, a3, a6, and a7 derived from 1000 bootstrap resamples across the two data integration strategies. The width of each violin indicates the sample density at different values, with a red line marking the ground truth. Dashed lines within each violin represent the median and interquartile range. Panels (b)-(e) show likelihood profiles for four parameters in the Lotka-Volterra model (a2, a3, a6, and a7), comparing two data integration strategies (standard and CrossLabFit approach) against the ground truth to assess parameter identifiability. These panels plot against parameter values, indicating that minima closer to the ground truth represent more accurate estimates.