Deep learning for biology

The brain's neural network has long inspired artificial-intelligence researchers.Credit: Alfred Pasieka/SPL/Getty Four years ago, scientists from Google showed up on neuroscientist Steve Finkbeiner's doorstep. The researchers were based at Google Accelerated Science, a research division in Mountain View, California, that aims to use Google technologies to speed scientific discovery. They were interested in applying'deep-learning' approaches to the mountains of imaging data generated by Finkbeiner's team at the Gladstone Institute of Neurological Disease in San Francisco, also in California. Deep-learning algorithms take raw features from an extremely large, annotated data set, such as a collection of images or genomes, and use them to create a predictive tool based on patterns buried inside. Once trained, the algorithms can apply that training to analyse other data, sometimes from wildly different sources.