Artificial Intelligence Medical Compendium

Deep learning co-folding and docking models accurately predict ligand binding poses at orthosteric sites yet systematically underperform at allosteric pockets. Here, we demonstrate that this accuracy gap reflects a fundamental biophysical property of... read more 

Traditional cell tracking methods focus on fully automated tracking. The quality of the generated tracks, however, is heavily influenced by factors such as cell speed and density. In complex scenarios where track correctness is essential, an efficien... read more 

Dengue virus (DENV) causes dengue fever, a globally prevalent, epidemic-prone disease with no FDA-approved antivirals. Additionally, the available vaccine for DENV can increase the risk of severe dengue fever for those who have never had a DENV infec... read more 

Accurate treatment selection remains a major challenge in precision oncology because tumors with similar genomic alterations can respond differently to therapy. Most drug-response models evaluate individual drugs or drug-sample pairs, whereas clinica... read more 

Sex differences are pervasive across the animal kingdom1,2, shaped by reproductive strategies, ecological roles, and physiological demands. Neurobiological studies have largely focused on sex differences in reproduction and aggression3,4, leaving und... read more 

Genomic foundation models (GFMs) are pretrained on large genomic datasets, but their ability to predict rare disease-associated events after fine-tuning remains unclear. We tested this using TDP-43 cryptic exons, well characterized splicing events li... read more 

Background: Epigenetic deregulation is a defining feature of leukemia, and DNA methylation and chromatin accessibility profiles encode the cell of origin, lineage and clinical behaviour of the disease. Artificial intelligence (AI) and machine learnin... read more 

The self-splicing group I intron ribozyme from Tetrahymena thermophillia (THr) is a prototypical example of how RNA overcomes its limited chemical repertoire to form complex, negatively charged junctions and catalyze chemical reactions. Despite over ... read more 

High-content imaging-based screens with small molecule or genetic perturbations rely on rich optical phenotypes, yet how distinct subcellular markers contribute complementary biological information remains unclear. Here, we introduce CellMAPP, a mult... read more 

Background: More than 90% of rare diseases lack an approved therapy, partly reflecting economic barriers in developing treatments for small patient populations. A common bottleneck is costly and resource-intensive hit-to-lead prioritization. Congenit... read more