Maria Lopopolo

DIANA predicts metadata categories from ancient metagenomics data, achieving high accuracy in host, community type, and material classification.

The paper adds standardized radiocarbon dating information to the AncientMetagenomeDir dataset, highlighting inconsistencies in radiocarbon reporting across ancient metagenomic studies.

The paper identifies a de novo enhancer mutation in KCNB1 causing ST Depression Syndrome, a cardiac arrhythmia, and shows it can be predicted by a deep neural network.

This study evaluates the ability of long-read sequencing to detect somatic variants in a lymphoma patient, highlighting the need for specialized tools and the advantages of long reads for structural variants.