Using the antibody-antigen binding interface to train image-based deep neural networks for antibody-epitope classification
Fig 9
Detection of clonally diverse antibodies using the OCC method RCAE.
a This number corresponds to the ranking assigned to the 100 DNN models based on the AUROC score computed on the testing set. b Image reconstruction errors ranked from low to high. Gray circles are associates with fingerprints from anomalous Abs. Colored circles highlight clusters of errors for fingerprints of the Abs from the “normal” class. Note that the graphs only display the reconstruction errors of 120 fingerprints from each testing set. c The test sets used to evaluate the DNN models below contained only Abs that do not compete with KZ52 in an attempt to detect false positives (i.e., the Ab representing the normal class was a decoy).