Marco Raffaele Cosenza

The paper shows that escaping replicative crisis and achieving immortality precedes complex genome evolution in cancer cells.

The paper shows that autophagy selectively degrades micronuclei with nuclear envelope defects, preventing chromosomal instability by eliminating missegregated chromosomal material.

This paper reviews current smart microscopy implementations and proposes a framework for interoperability to improve collaboration and standardization in the field.

The paper introduces MAGIC, a platform combining imaging and genomics to study de novo chromosome rearrangements, finding that dicentric chromosomes initiate CA events and TP53 deficiency increases CA rates.

This paper introduces DLVPM, a deep learning method for integrating multi-modal cancer data, showing improved performance in mapping associations between genetic, epigenetic, and histological features.

MosaiCatcher v2 provides a standardized workflow for single-cell structural variation detection using Strand-seq, enhancing reproducibility and portability in human genetics research.