<?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-selin-erdem</title><link>https://pages.htgaa.org/2026a/selin-erdem/homework/week-07-hw-genetic-circuits-part-ii/index.html</link><description>Assignment Part 1: Intracellular Artificial Neural Networks:
What advantages do IANNs have over traditional genetic circuits, whose input/output behaviors are Boolean functions? Graded Response vs. Binary Logic: Traditional circuits work like a light switch (ON or OFF). IANNs work like a dimmer switch; they can process analog signals, allowing the cell to respond to varying concentrations of a molecule rather than just its presence or absence.
Signal Integration (Weighting): In a perceptron model, different inputs can have different “weights.” This means the cell can prioritize one environmental signal (like a toxin) over another (like a nutrient) before making a final decision.</description><generator>Hugo</generator><language>en</language><atom:link href="https://pages.htgaa.org/2026a/selin-erdem/homework/week-07-hw-genetic-circuits-part-ii/index.xml" rel="self" type="application/rss+xml"/></channel></rss>