Zero-shot prediction of drug responses using biologically informed neural networks trained on phosphoproteomic timeseries
Fig 2
Model performance on interpolation tasks for time-resolved phosphoproteomics data.
A. EGF-stimulation phosphoproteomics data and model fits across time points, values clipped between -3 and 3. B. Distribution of absolute distances between consecutive timepoints for the experimental data (median = 0.27, mean = 0.38) and model fits (median = 0.05, mean = 0.17). Dashed lines indicate the medians. The difference between both distributions is statistically significant (permutation test, 10,000 resamples, p = 0.0001). C. Comparison of interpolation performance on held-out time-points between linear interpolation, anchor estimation using data from a single phosphosite (GAB1:S266s), and one-to-one mapping. Black boxes on the X-axis indicates the time points held out during training. D. Selected examples of time series data compared to model fits and predictions at the 4 min time point. Lines indicate means; ribbons standard deviations.