Let it RE:IN: integrating experimental observations to predict pluripotency network behaviour

Our ability to reprogram cells and induce transitions between states has fast become a commonplace tool, but our understanding of the underlying processes and capacity to predict these is still relatively rudimentary. A new article by Dunn et al () combines a computational reasoning approach with experimental observation to construct a network-level understanding of the transcription factors instructing acquisition of naïve pluripotency during reprogramming.