hi I’m grant ⍾ and welcome to my blog! Learning to Adapt ⚶ is a blog about learning– the biological kind! (sorry, machines).
Who am I
I’m grant ⍾. I studied bioengineering and worked in biotech for a few years, helping build microscopes and look at molecules. I built my identity around my ability to learn and held a belief that anybody could could gain any skill– until I couldn’t. Simultaneously, I was working with inverse design software (Zemax), reigniting a passion for computational biology, and developing a perspective on biological systems that sparked my curiosity.
What I’m studying
Complex systems are systems with many components where each part behaves according to simple, predictable rules yet the whole is unpredictable, hard to describe, and gives rise to novel features. Alternatively, they are systems that you could find yourself talking about at lengths, even when you try to keep it short. We find ourselves in a world enriched with complexity and have managed to build some complex systems ourselves.
Biology has built a number of complex systems and has done so for billions of years. These systems are some of the most persistent things we know, and I believe that by studying how they work, how they’re built, and how they change, we can better understand how to build persistent systems of our own. I’ve long had a fascination with computational biology and watching intricate structures emerge from simple rules.
Learning is the process by which behavior changes in response to the acquisition of knowledge about the world, encoded in memory. (kandel, principles of neural science)
How I’m doing it
I’m going to be showcasing a couple tools. Python mostly.
What I’m reading:
Here’s a list of books that I’m reading from at the moment.
Principles of Neural Science, 5e; Kandel, Schwartz
Developmental Biology, 13e; Barrsei, Gilbert
Physical Biology of the Cell, 2e, Phillips, Kondev, Theriot, Garcia
Information Theory, Inference, and Learning Algorithms, 7.2; MacKay
Statistical Mechanics, Entropy, Order Parameters, and Complexity, 2e; Sethna
Molecular Driving Forces: Statistical Thermodynamics in Biology, Chemistry, Physics, and Nanoscience, 2e; Dill, Bromberg
Evolutionary Neuroscience, 2e; Kaas: my main reference on evolution of the vertebrate nervous system.
Vertebrate Life, 9e; Pough, Janis, Heiser
Biology of the Invertebrates, 7e; Pechenik
Introduction to Systems Biology, 2e; Alon
Wikipedia: the whole thing. support our queen
Disclaimer: This is a blog (not a journal) and I post posts (not papers)! I can be wrong, I haven’t read all literature yet, and I love to speculate. Please feel free to contact me at {email} with any corrections, concerns, or feedback!