<?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-henrietta-scholtz</title><link>https://pages.htgaa.org/2026a/henrietta-scholtz/homework/week-07-hw-genetic-circuits-part-ii/index.html</link><description>Intracellular Artificial Neural Networks (IANNs) What advantages do IANNs have over traditional genetic circuits,whose input/output behaviors are Boolean functions?
Boolean genetic circuits are binary; a signal is either present or absent, on or off. IANNs add nuance by incorporating quantity: not just whether a signal is present, but how much, and how that amount combines with other weighted inputs to determine output. This matters biologically because cells are not rigid systems. Gene expression fluctuates due to stochastic noise and biological drift. Boolean circuits are brittle in this context, while IANNs, by distributing computation across many weighted inputs, are more robust to that natural variability.</description><generator>Hugo</generator><language>en</language><atom:link href="https://pages.htgaa.org/2026a/henrietta-scholtz/homework/week-07-hw-genetic-circuits-part-ii/index.xml" rel="self" type="application/rss+xml"/></channel></rss>