One of my main scientific goals is the application of mathematical models to find interesting insights into biological systems. This is a really broad goal, as depending on the area, there may be very different ways to gain insight. Here, I want to discuss one example, an interesting paper by Sriram and coworkers that was published in PLOS Computational Biology last year entitled "Modeling cortisol dynamics in the neuro-endocrine axis distinguishes normal, depression, and post-traumatic stress disorder (PTSD) in humans".
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Very recently, I've been intrigued by control theory applied to systems biology. This strategy seems to often produce insightful and unintuitive results. In this blog post, I'm going to take a look at a very cool article by Ben-Zvi and coworkers that applies control theory to a mathematical model of the hypothalamic-pituitary-adrenal (HPA) axis, and hopefully put it in a bit of a broader context.
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In 1957, we knew what DNA was. We were pretty sure that proteins were determined by sequences of DNA. But we didn't know exactly how this happened. In other words, the genetic code was still a mystery back then. This was a particularly perplexing problem, because a very simple question could be stated with no obvious answer: How does a language (DNA sequences) with four letters (the nucleotides A, C, G, and T) get translated into a language (protein sequences) with twenty letters (amino acids)... and furthermore, is there some higher purpose to having these two different alphabets?
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