<?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 :: 2026a-john-adeyemo-adedeji</title><link>https://pages.htgaa.org/2026a/john-adeyemo-adedeji/weeks/week-07/index.html</link><description>Class Assignment — Week 7 Part A. Intracellular Artificial Neural Networks (IANNs) 1. Advantages of IANNs over Boolean Genetic Circuits Boolean genetic circuits are fundamentally limited by their design logic: every input gets collapsed into a binary state, and the circuit operates on those discrete values. That works for simple switch-like decisions, but most physiologically relevant signals (metabolite concentrations, osmotic gradients, and quorum sensing molecule titres), exist on a continuum, and forcing them through a hard threshold discards information. IANNs avoid this by processing analog inputs directly, generating graded outputs that reflect the actual magnitude of the input rather than just which side of a threshold it fell on.</description><generator>Hugo</generator><language>en</language><atom:link href="https://pages.htgaa.org/2026a/john-adeyemo-adedeji/weeks/week-07/index.xml" rel="self" type="application/rss+xml"/></channel></rss>