Gabriel Arantes dos Santos

The paper shows processed pseudogenes are dynamic evolutionary elements, not inert, and links their abundance to life-history traits and cancer-related dynamics across vertebrates.

This study examines transcriptomic entropy in aging and cancer, finding tissue-specific entropy changes and its association with cancer progression and survival outcomes.

The paper assigns stemness scores to human tissues using machine learning and finds a general decline in stemness with age, except in the uterus, and links stemness to proliferation and senescence.

The paper updates six databases in the Human Ageing Genomic Resources (HAGR) focusing on genes, drugs, and genetic variants related to ageing and longevity.

This study identifies a loss of cell identity in ageing and cancer using transcriptomic data, showing distinct patterns in gene expression associated with patient survival.