Scientists used machine learning to analyze the coevolution of physical traits in butterflies.

The latest machine learning models can identify many visual and molecular features of a particular cancer. If the technology advances to the clinic, it could help diagnose patients and predict survival.

Machine learning can analyze photographs of cancer, tumor pathology slides, and genomes. Now, scientists are poised to integrate that information into cancer uber-models.

Machine learning could be the key to reducing the use of animals in experiments.

Researchers are developing computational approaches to extract information from multiple sets of single-cell sequencing data.

Researchers develop an app that can estimate the biological age of a rodent from its mug shot—and could give a boost to the science of human aging in the process.

A junk mail filter can learn to pick out six behaviors of hydras by analyzing hours of video footage.

The use of underperforming computational tools is a major offender in science’s reproducibility crisis—and there’s growing momentum to avoid it.

Machine-learning algorithms can automate the analysis of cell images and data.