Lecture Notes and exercises
Prolog
A lecture by Joshua M. Epstein in which he treats some enduring misconceptions about modeling. One of these is that the goal is always prediction. The lecture distinguishes between explanation and prediction as modeling goals, and offers sixteen reasons other than prediction to build a model. It also challenges the common assumption that scientific theories arise from and 'summarize' data, when often, theories precede and guide data collection; without theory, in other words, it is not clear what data to collect. Among other things, it also argues that the modeling enterprise enforces habits of mind essential to freedom.
How to solve ordinary differential equations? (tutorials in various common programing enviourments)
Lecture 1 - Epidemiology of COVID-19 (Notes, Recording)
- Basic simulation of the SIR model (Python,Mathematica)
Lecture 2 - The insulin-glucose circuit (Notes, Recording)
Lecture 3 - Beta-cell tissue size control has fragilities that lead to type-2 diabetes: Dynamical compensation and mutant resistance in tissues (Notes, Recording)
Exercise 2 - Solution (by Alon Bar)
Lecture 4 - Two-gland feedback in the stress-hormone axis generates seasonal clocks and explains clinical phenomena with a timescale of months (Notes, Recording)
Lecture 5 - Addiction (Notes, Recording)
Exercise 3 -Solution (by Alon Bar)
Lecture 6 - The immune system detects exponential threats (Notes, Recording)
Lecture 7 - Autoimmune disease as a fragility of surveillance against hyper-secreting mutants (Notes, Recording)
Lecture 8 - Inflammation and fibrosis as a bistable system (Notes, Recording)
Lecture 9 - Basic facts of aging (Notes, Recording)
Lecture 10 - Aging and the saturation of damage removal (Notes, Recording)
Lecture 11 - Aging-related diseases and their exponentially rising incidence with age. (Notes, Recording)
Lecture 12 - Periodic table of diseases (Notes, Recording)