https://pages.htgaa.org/2026a/domenica-lilia-vizcaino-andrade/homework/week-07-hw-genetic-circuits-part-ii/index.htmlPart 1: Intracellular Artificial Neural Networks (IANNs) What advantages do IANNs have over traditional genetic circuits, whose input/output behaviors are Boolean functions? There is currently a need for non-binary biological computing, where an input for example is analog, or we want an output to be graded, this is where Intracellular Artificial Neural Networks are useful. This means that outputs can be low, medium, high. We can manupulate the inputs/outputs as if they were signals (using low-pass, high-pass, band-pass, etc filters) and with mathematical functions, rather than strictly Boolean ON/OFF outputs. IANNs combine many inputs simultaneously, and each input has a different “weight”. They can also detect patterns that are nonlinear and create thresholds. IANNs also help with scalability, as we can include many layers (multi-layers) while dealing with boolean circuits, and gates can get very messy.Hugoen