What machine learning can do for developmental biology

ABSTRACT Developmental biology has grown into a data intensive science with the development of high-throughput imaging and multi-omics approaches. Machine learning is versatile set techniques that can help make sense these large datasets minimal human intervention, through tasks such as image segmentation, super-resolution microscopy cell clustering. In this Spotlight, I introduce key concepts, advantages limitations machine learning, discuss how methods are being applied to problems in developmental biology. Specifically, focus on improving single-cell ‘omics’ analysis. Finally, provide an outlook for futures fields suggest ways foster new interdisciplinary developments.