<?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-florian-kroh</title><link>https://pages.htgaa.org/2026a/florian-kroh/homework/week-07-hw-genetic-circuits-part-ii/index.html</link><description>Part 1 What advantages do IANNs have over traditional genetic circuits, whose input/output behaviors are Boolean functions? The key advantage of intracellular analog neural networks (IANNs) over traditional genetic circuits lies in the shift from discrete logic to continuous computation. Classical genetic circuits are typically engineered as Boolean systems: inputs are interpreted as “on” or “off”. This abstraction is convenient for engineering and design, but it is fundamentally misaligned with how biology actually operates, where signals exist as continuously varying concentrations and reaction rates.</description><generator>Hugo</generator><language>en</language><atom:link href="https://pages.htgaa.org/2026a/florian-kroh/homework/week-07-hw-genetic-circuits-part-ii/index.xml" rel="self" type="application/rss+xml"/></channel></rss>