<?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 — Genetic Circuits Part II: Neuromorphic Circuits :: 2026a-katherine-silva</title><link>https://pages.htgaa.org/2026a/katherine-silva/homework/week-07-hw-genetic-circuits-part-ii/index.html</link><description>What advantages do IANNs have over traditional genetic circuits, whose input/output behaviors are Boolean functions? IANNs provide graded and analog computation rather than a strict ON/OFF logic. Enabling cells to integrate multiple inputs with tunable weights and produce continuous outputs that reflect the signal strength, not just presence/absence. IANNs can implement thresholding, nonlinear decision boundaries, and noise tolerance, making them more robust in heterogeneous biological environments. They also allow combinatorial regulation, which is difficult to achieve with simple Boolean gates without increasing the circuit complexity.</description><generator>Hugo</generator><language>en</language><atom:link href="https://pages.htgaa.org/2026a/katherine-silva/homework/week-07-hw-genetic-circuits-part-ii/index.xml" rel="self" type="application/rss+xml"/></channel></rss>