A collection of resources that apply formal systems to model biological processes. Some easily accessible books to understand the general approaches in this field are also included.
McCullouch and Pitts study of neurons in biology birthed the pivotal paper that kickstarted A.I., regular languages, and digital computers. It was the only paper included in the EDVAC report by John Von Neumann.
An interactive demo of their model is available here: https://justinmeiners.github.io/neural-nets-sim/
Reaction-Diffusion Systems
Neurocomics (Beginner)
Introducing Evolution (Beginner)
Introducing Genetics (Beginner)
Introducing Epigenetics (Beginner)
Complexity: A Very Short Introduction (Intermediate)
Games of Life (Intermediate)
- Rashevsky and Rosen
Rashevsky devised the primary model of neural networks which was interpreted using the boolean language by McCullough/Pitts. His student Robert Rosen went on to work on using Category Theory to model biology. These works need to be catalogued here. Herbert Simon was also his student.
There could also be more possible works from the conference where McCullough presented his work and met Pitts.
- Ilya Pregorine’s Work
- Gregory Chaitin’s work
- Stochastic CFG for RNA
- Knot Theory for Protein Molecules
- Wang Tiles and DNA
- Molecular Networks and Monomial Ideals
- Computational Modeling, Formal Analysis, and Tools for Systems Biology: Survey