Fig. 4: Performance comparison between TranPeakNet and traditional methods.
A Performance comparison between our proposed model and established traditional tools on randomly sampled molecules from the test dataset. Our model performs better across all molecular weight categories. The advantage of our approach is increasingly evident as molecular size increases. The overall result uses equal weight for the molecular weight categories. B Comparing our model, ChemDraw, and Mestrenova on two typical examples. A small molecule (a) with weight of ~250 Dalton and a larger molecule (b) with weight of ~500 Dalton. The observed experimental signals and the predicted signals are colored in blue and orange, respectively. The prediction error (MAEs) is shown in the bottom right corner of each plot. Our model performs better than ChemDraw and Mestrenova, and particularly excels in handling large molecules with complex conformations. C Description of the data used across molecular weight classes.
