A computer built using tens of thousands of living brain cells can recognise simple patterns of light and electricity. It could eventually be incorporated into a robot that also uses living muscle tissues. Artificially intelligent algorithms inspired by the brain called neural networks have been used for everything from chatbots to searching for new laws of physics.

This is the second post in the series Deep Learning for Life Sciences. In the previous one, I showed how to use Deep Learning on Ancient DNA. Today it is time to talk about how Deep Learning can help Cell Biology to capture diversity and complexity of cell populations. Single Cell RNA sequencing (scRNAseq) revolutionized Life Sciences a few years ago by bringing an unprecedented resolution to study heterogeneity in cell populations. The impact was so dramatic that Science magazine announced scRNAseq technology as the Breakthrough of the Year 2018.