<?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 2: Neuromorphic Circuits :: 2026a-mariana-kanbe</title><link>https://pages.htgaa.org/2026a/mariana-kanbe/homework/week-07-genetic-circuits-pt7/index.html</link><description>Assignment Part 1: Intracellular Artificial Neural Networks (IANNs) Question 1
Traditional genetic circuits are usually implemented in Boolean logic (ON/OFF), hand-designed as fixed logic. so representing nuanced behaviors often requires many gates, sharp thresholds, and careful tuning, which can make designs bulky and brittle. As the number of inputs grows the circuit complexity can explode combinatorially, increasing burden by stacking multiple layers and adding intermediate nodes, which increases metabolic load, failure points, and sensitivity to part-to-part variability Also, adapting to new targets or shifting biological context often means redesigning the circuit architecture, not just re-tuning parameters.</description><generator>Hugo</generator><language>en</language><atom:link href="https://pages.htgaa.org/2026a/mariana-kanbe/homework/week-07-genetic-circuits-pt7/index.xml" rel="self" type="application/rss+xml"/></channel></rss>