Evolutionary graph theory solves the longstanding puzzle of why diverse infectious diseases and cancers show similar (approximately lognormal) distributions of their incubation periods.

A simple model reveals the roles of colony geometry and diffusion rate in allowing microbes to cooperate by sharing public goods.

A general framework captures the evolutionary routes leading to the formation and progression of tumors.

Mathematical modeling shows that reproductive specialization is strongly favored in sparse networks of cellular interactions that reflect the morphology of early multicellular organisms, even when benefits of specialization are saturating.

Advanced orthology clustering of bilaterian and non-bilaterian sequences identifies 157 bilaterian-specific genes which are linked to key morphological features of this animal group.

An evolutionary algorithm is used to build gene networks implementing cell size control, and suggests multiple ways for evolution to first build sizers and turn them into adders depending on evolutionary constraints.

Integration of language model and geometric deep learning enables accurate and efficient genome-scale annotation of comprehensive protein-ligand binding sites.

The coalescent history of a population can be learned just from the present genomic diversity, without having detailed prior knowledge of the pattern of recombination or the forces driving coalescence.

Mapping single-cell atlases throughout Metazoa systematically characterizes cell type diversity and the evolution of their associated gene expression programs.