Fig. 2: Performance evaluation of SEMORE clustering module on classification of three diverse types of morphologies inspired by biological systems.

a Three classes of time-resolved aggregations were simulated to capture a broad aspect of biological systems (see Methods): isotropic, where aggregates grow radially, where aggregates grow in response to steric hindrance and branching fibrils where aggregates grow linearly followed by branching. The three inserts depict the general pipeline for cluster identification: From left to right Aggregates with diverse final morphologies are produced in a frame-by-frame manner, with the amount and locations of particles randomly drawn based on previous localizations and start and end times randomly drawn. Uniform noise is added in all three dimensions (x, y, time). The model accurately predicts diverse aggregates, showcased by different colours. The black point corresponds to data points predicted as the wrong label, i.e., either noise predicted as an aggregate point or multiple predicted aggregates for the same ground truth label (FP) while the brown points correspond to aggregational locations predicted as noise (FN). b Quantification of operational performance by a confusion matrix. Predictions are shown from 50 experiments for each aggregation type, each containing 10 individual aggregations for isotropic and random, and 25 for fibril growth. Errors are standard deviations calculated across accuracies for each individual aggregate. Common classification metrics for the evaluation are shown in the table on the right side of the corresponding confusion matrix. Source data are provided as a Source Data file.