<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Week 7 HW: Genetic Circuits Part II :: 2026a-alayah-hines</title><link>https://pages.htgaa.org/2026a/alayah-hines/homework/week-07-hw-genetic-circuits-part-ii/index.html</link><description>HW7 Intracellular Artificial Neural Networks What advantages do IANNs have over traditional genetic circuits, whose input/output behaviors are Boolean functions? Intracellular Artificial Neural Networks use continuous analog signals instead of binary ones, which allows them to understand complex inputs like concentrations as opposed to just noting presence. They can use this to perform thresholding, enabling more complex reactions with fewer components. Overall, they are more scalable and better at multi-input sensing than regular genetic circuits.</description><generator>Hugo</generator><language>en</language><atom:link href="https://pages.htgaa.org/2026a/alayah-hines/homework/week-07-hw-genetic-circuits-part-ii/index.xml" rel="self" type="application/rss+xml"/></channel></rss>