The growth of publicly accessible data troves on genome sequences, gene activity, and protein structures and interactions has opened new territory for biologists. Seizing on advances in computational power, data storage, and software algorithms able to separate the wheat from the chaff, researchers are making fundamental discoveries without ever filling a pipette, staining a cell or dissecting an animal. Thanks to a National Science Foundation–funded initiative called the iPlant Collaborative, for example, there's an emerging generation of data-analyzing "plant biologists" who have never gotten their hands dirty digging in soil or watering seeds. And the National Institutes of Health recently announced plans to sink $96 million into boosting analysis of big data. "There is a transformation happening in biology," says Daniel Geschwind, a neurogeneticist at the University of California, Los Angeles.