Phys.org  November 14, 2022 Neuro-inspired models can transform synthetic gene circuit design in a manner that is reliable, efficient in resource utilization, and readily reconfigurable for different tasks. To this end, an international team of researchers (Israel, USA – MIT) has introduced the perceptgene, a perceptron that computes in the logarithmic domain, which enables efficient implementation of artificial neural networks in Escherichia coli cells. They successfully modified perceptgene parameters to create devices that encode a minimum, maximum, and average of analog inputs. With these devices, they created multi-layer perceptgene circuits that compute a soft majority function, perform an analog-to-digital conversion, […]