<?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-karol-duque</title><link>https://pages.htgaa.org/2026a/karol-duque/homework/week-07-hw-genetic-circuits-part-ii/index.html</link><description>Part 1: Intracellular Artificial Neural Networks (IANNs)
What advantages do IANNs have over traditional genetic circuits, whose input/output behaviors are Boolean functions? Traditional genetic circuits implement Boolean logic using transcription factors, promoters, and other regulatory elements. Their input/output behavior is inherently digital (ON/OFF), and they often suffer from limited computational capacity, scalability issues, and lack of analog processing. Only simple logic functions (AND, OR, NOT) can be composed. Wiring many gates leads to metabolic burden, crosstalk, and slow response times. They also cannot perform weighted sums or continuous transformations.</description><generator>Hugo</generator><language>en</language><atom:link href="https://pages.htgaa.org/2026a/karol-duque/homework/week-07-hw-genetic-circuits-part-ii/index.xml" rel="self" type="application/rss+xml"/></channel></rss>