Do filtered circular fingerprints improve either prediction or runtime performance while retaining interpretability?
Circular fingerprints are potent structural features that yield highly predictive models and encode interpretable structural information. However, to not lose interpretability, circular fingerprints should not be folded when building prediction models. Our experiments show that filtering is a suitable option to reduce the high computational effort when working with all fingerprint fragments. Additionally, our experiments suggest that the area under precision recall curve is a more sensible statistic for validating (Q)SAR models for virtual screening than the area under ROC or other measures for early recognition.
These facts suggested that an immature immune response or tolerance to H. pylori exists in childhood and serodiagnosis of H. pylori infection is less useful in children aged below 10.