1. Physics 414: Introduction to Biophysics Professor Henry Greenside December 7, 2017

2. At the backboard: linear stability analysis of differential equations and of partial differential equations
Cases to discuss:
One-variable differential equation du/dt = f(u(t))
Multivariable differential equation du/dt = f(u(t)) , u = (u1, u2, …, uN)
Single variable one-space-dimension partial differential equation \partial_t u(t,x) = f(u) + D \partial_x^ Cannot get cellular pattern formation no matter what is f(u)
Two variable one-space-dimension pde (case of Turing instability)
Answer is The green dot is about 2/3 of the way between 0.01 and 0.1 so the 0.01 value is multiplied by 10^(2/3) = 100^(1/3). Since 4^3 = 64 and 5^3 = 125, 100^(1/3) is less than but closer to 125, so estimated value is 5 * 0.01 = 0.05.
To two significant digits, 100^(1/3) = 0.47.
Where some tickmarks would lie Log[10,2] = 0.3 or about 1/3 from the left
Log[10,3] = 0.48 or about 0.5
Log[10,4] = 0.60
Log[10,5] = 0.70
Log[10,6] = 0.78
Log[10,7] = 0.85
Log[10,8] = 0.90
Log[10,9] = 0.95

3. For dynamical system of two coupled reactions, stability determined by signs of trace and determinant
Answer is The green dot is about 2/3 of the way between 0.01 and 0.1 so the 0.01 value is multiplied by 10^(2/3) = 100^(1/3). Since 4^3 = 64 and 5^3 = 125, 100^(1/3) is less than but closer to 125, so estimated value is 5 * 0.01 = 0.05.
To two significant digits, 100^(1/3) = 0.47.
Where some tickmarks would lie Log[10,2] = 0.3 or about 1/3 from the left
Log[10,3] = 0.48 or about 0.5
Log[10,4] = 0.60
Log[10,5] = 0.70
Log[10,6] = 0.78
Log[10,7] = 0.85
Log[10,8] = 0.90
Log[10,9] = 0.95

4. At the blackboard: can now work out efficiently details of Turing instability (see Cross + Greenside pages )
Eigenvalues are complex above this parabola, corresponding to oscillatory dynamics of small perturbations
Answer is The green dot is about 2/3 of the way between 0.01 and 0.1 so the 0.01 value is multiplied by 10^(2/3) = 100^(1/3). Since 4^3 = 64 and 5^3 = 125, 100^(1/3) is less than but closer to 125, so estimated value is 5 * 0.01 = 0.05.
To two significant digits, 100^(1/3) = 0.47.
Where some tickmarks would lie Log[10,2] = 0.3 or about 1/3 from the left
Log[10,3] = 0.48 or about 0.5
Log[10,4] = 0.60
Log[10,5] = 0.70
Log[10,6] = 0.78
Log[10,7] = 0.85
Log[10,8] = 0.90
Log[10,9] = 0.95
Shaded region is real part of eigenvalues both negative, so stable region.
Instability can occur by real eigenvalue changing from negative to positive, or real part of complex eigenvalue changing from negative to positive (oscillatory instability)

5. Brusselator: historically important model of chemical pattern formation, although no corresponding experiment
Assume A, B concentrations so large that they can be treated as constant parameters, then only X and Y concentrations change with time.
Answer is The green dot is about 2/3 of the way between 0.01 and 0.1 so the 0.01 value is multiplied by 10^(2/3) = 100^(1/3). Since 4^3 = 64 and 5^3 = 125, 100^(1/3) is less than but closer to 125, so estimated value is 5 * 0.01 = 0.05.
To two significant digits, 100^(1/3) = 0.47.
Where some tickmarks would lie Log[10,2] = 0.3 or about 1/3 from the left
Log[10,3] = 0.48 or about 0.5
Log[10,4] = 0.60
Log[10,5] = 0.70
Log[10,6] = 0.78
Log[10,7] = 0.85
Log[10,8] = 0.90
Log[10,9] = 0.95
In Assignment 8, you study its fixed points, when fixed points are stable in absence of diffusion, and how diffusion can cause instability leading to a cellular pattern (Turing instability).

6. Linear stability analysis of the Brusselator predicts a spatially uniform fixed point becomes unstable to spatial oscillations at a particular wave length: cells:
Answer is The green dot is about 2/3 of the way between 0.01 and 0.1 so the 0.01 value is multiplied by 10^(2/3) = 100^(1/3). Since 4^3 = 64 and 5^3 = 125, 100^(1/3) is less than but closer to 125, so estimated value is 5 * 0.01 = 0.05.
To two significant digits, 100^(1/3) = 0.47.
Where some tickmarks would lie Log[10,2] = 0.3 or about 1/3 from the left
Log[10,3] = 0.48 or about 0.5
Log[10,4] = 0.60
Log[10,5] = 0.70
Log[10,6] = 0.78
Log[10,7] = 0.85
Log[10,8] = 0.90
Log[10,9] = 0.95

7. Brusselator without diffusion for parameters of Turing instability has oscillatory (periodic) dynamics
u,v
Answer is The green dot is about 2/3 of the way between 0.01 and 0.1 so the 0.01 value is multiplied by 10^(2/3) = 100^(1/3). Since 4^3 = 64 and 5^3 = 125, 100^(1/3) is less than but closer to 125, so estimated value is 5 * 0.01 = 0.05.
To two significant digits, 100^(1/3) = 0.47.
Where some tickmarks would lie Log[10,2] = 0.3 or about 1/3 from the left
Log[10,3] = 0.48 or about 0.5
Log[10,4] = 0.60
Log[10,5] = 0.70
Log[10,6] = 0.78
Log[10,7] = 0.85
Log[10,8] = 0.90
Log[10,9] = 0.95
time t
The fixed point (u,v) = (a,b/a) becomes linearly unstable when b > 1 + a^2. Here a tiny perturbation of was added to u* = a and you can see the perturbation grow in magnitude until large-scale periodic oscillations arise.

8. Numerical simulations confirm the linear stability prediction and show what is the nonlinear steady cellular state
Discretize time in equal small intervals Dt: t = i Dt, i = 0, 1, …, nt = T/Dt
Discretize space in equal small intervals Dx: x = j Dx(j – 1) , i = 1, 2, …, nx = L/Dx + 1
Approximate time-derivative by 1st-order accurate finite difference (“forward Euler method”):
Du/dt ~ ( u(i+1,j) – u(i,j) ) / Dt
Approximate second-order derivative of diffusion by 2nd-order-accurate finite difference:
d^2 u / dx^2 ~ ( u(i,j+1) – 2 u(i,j) + u(i,j-1) ) / Dx^2
Some subtleties related to how to implement boundary conditions at i=1 and j=nx.
Above leads to a so-called explicit iterative numerical method: given current information over all of space at time t (time index I) and boundary conditions, this method leads to a simple estimate of the spatial stucture at time t+Dt a short step into the future (time index i+1). Using spatial information at time i+1 as the initial condition for the next step then gives the spatial information at step i+2, and so on.
Simple to program, quick to run but has a big flaw: algorithm becomes numerically unstable (numerical solution diverges exponentially rapidly from exact solution) if Dt >~ (1/D) Dx^2, i.e., the constant time step has to be smaller than an order-1 number times Dx^2. So fine spatial resolution requires extremely small time steps which is inefficient. Takes some trial and error to choose spatial and time resolutions to balance efficiency (few time steps, few spatial mesh points) and accuracy.
Download and play with Mma notebook 1d-brusselator-integration.nb
Answer is The green dot is about 2/3 of the way between 0.01 and 0.1 so the 0.01 value is multiplied by 10^(2/3) = 100^(1/3). Since 4^3 = 64 and 5^3 = 125, 100^(1/3) is less than but closer to 125, so estimated value is 5 * 0.01 = 0.05.
To two significant digits, 100^(1/3) = 0.47.
Where some tickmarks would lie Log[10,2] = 0.3 or about 1/3 from the left
Log[10,3] = 0.48 or about 0.5
Log[10,4] = 0.60
Log[10,5] = 0.70
Log[10,6] = 0.78
Log[10,7] = 0.85
Log[10,8] = 0.90
Log[10,9] = 0.95

9. Segments of Mathematica code for integrating Brusselator with finite differences
Answer is The green dot is about 2/3 of the way between 0.01 and 0.1 so the 0.01 value is multiplied by 10^(2/3) = 100^(1/3). Since 4^3 = 64 and 5^3 = 125, 100^(1/3) is less than but closer to 125, so estimated value is 5 * 0.01 = 0.05.
To two significant digits, 100^(1/3) = 0.47.
Where some tickmarks would lie Log[10,2] = 0.3 or about 1/3 from the left
Log[10,3] = 0.48 or about 0.5
Log[10,4] = 0.60
Log[10,5] = 0.70
Log[10,6] = 0.78
Log[10,7] = 0.85
Log[10,8] = 0.90
Log[10,9] = 0.95

10. Parameters used in 1d Brusselator calculation
Answer is The green dot is about 2/3 of the way between 0.01 and 0.1 so the 0.01 value is multiplied by 10^(2/3) = 100^(1/3). Since 4^3 = 64 and 5^3 = 125, 100^(1/3) is less than but closer to 125, so estimated value is 5 * 0.01 = 0.05.
To two significant digits, 100^(1/3) = 0.47.
Where some tickmarks would lie Log[10,2] = 0.3 or about 1/3 from the left
Log[10,3] = 0.48 or about 0.5
Log[10,4] = 0.60
Log[10,5] = 0.70
Log[10,6] = 0.78
Log[10,7] = 0.85
Log[10,8] = 0.90
Log[10,9] = 0.95

11. Numerical simulations confirm the linear stability prediction and reveal what is the asymptotic nonlinear steady cellular state u x t v
Answer is The green dot is about 2/3 of the way between 0.01 and 0.1 so the 0.01 value is multiplied by 10^(2/3) = 100^(1/3). Since 4^3 = 64 and 5^3 = 125, 100^(1/3) is less than but closer to 125, so estimated value is 5 * 0.01 = 0.05.
To two significant digits, 100^(1/3) = 0.47.
Where some tickmarks would lie Log[10,2] = 0.3 or about 1/3 from the left
Log[10,3] = 0.48 or about 0.5
Log[10,4] = 0.60
Log[10,5] = 0.70
Log[10,6] = 0.78
Log[10,7] = 0.85
Log[10,8] = 0.90
Log[10,9] = 0.95 x t

12. In two spatial dimensions, Turing instability can lead to cellular patterns involving stripes, rectangles, and hexagon
Answer is The green dot is about 2/3 of the way between 0.01 and 0.1 so the 0.01 value is multiplied by 10^(2/3) = 100^(1/3). Since 4^3 = 64 and 5^3 = 125, 100^(1/3) is less than but closer to 125, so estimated value is 5 * 0.01 = 0.05.
To two significant digits, 100^(1/3) = 0.47.
Where some tickmarks would lie Log[10,2] = 0.3 or about 1/3 from the left
Log[10,3] = 0.48 or about 0.5
Log[10,4] = 0.60
Log[10,5] = 0.70
Log[10,6] = 0.78
Log[10,7] = 0.85
Log[10,8] = 0.90
Log[10,9] = 0.95
To see dynamics and how pattern evolves from different random initial conditions, in Safari on Mac, run Java applets on Mike Cross’s webpage

13. One last example: phyllotaxis pattern formation of branches, leaves, stems petals
Answer is The green dot is about 2/3 of the way between 0.01 and 0.1 so the 0.01 value is multiplied by 10^(2/3) = 100^(1/3). Since 4^3 = 64 and 5^3 = 125, 100^(1/3) is less than but closer to 125, so estimated value is 5 * 0.01 = 0.05.
To two significant digits, 100^(1/3) = 0.47.
Where some tickmarks would lie Log[10,2] = 0.3 or about 1/3 from the left
Log[10,3] = 0.48 or about 0.5
Log[10,4] = 0.60
Log[10,5] = 0.70
Log[10,6] = 0.78
Log[10,7] = 0.85
Log[10,8] = 0.90
Log[10,9] = 0.95

14. Anti-diffusive (up-gradient) active transport of auxin hormone determines cell differentiation
Answer is The green dot is about 2/3 of the way between 0.01 and 0.1 so the 0.01 value is multiplied by 10^(2/3) = 100^(1/3). Since 4^3 = 64 and 5^3 = 125, 100^(1/3) is less than but closer to 125, so estimated value is 5 * 0.01 = 0.05.
To two significant digits, 100^(1/3) = 0.47.
Where some tickmarks would lie Log[10,2] = 0.3 or about 1/3 from the left
Log[10,3] = 0.48 or about 0.5
Log[10,4] = 0.60
Log[10,5] = 0.70
Log[10,6] = 0.78
Log[10,7] = 0.85
Log[10,8] = 0.90
Log[10,9] = 0.95

15. Transport of auxin at the cellular level
Answer is The green dot is about 2/3 of the way between 0.01 and 0.1 so the 0.01 value is multiplied by 10^(2/3) = 100^(1/3). Since 4^3 = 64 and 5^3 = 125, 100^(1/3) is less than but closer to 125, so estimated value is 5 * 0.01 = 0.05.
To two significant digits, 100^(1/3) = 0.47.
Where some tickmarks would lie Log[10,2] = 0.3 or about 1/3 from the left
Log[10,3] = 0.48 or about 0.5
Log[10,4] = 0.60
Log[10,5] = 0.70
Log[10,6] = 0.78
Log[10,7] = 0.85
Log[10,8] = 0.90
Log[10,9] = 0.95

16. What have we learned over the semester?
Answer is The green dot is about 2/3 of the way between 0.01 and 0.1 so the 0.01 value is multiplied by 10^(2/3) = 100^(1/3). Since 4^3 = 64 and 5^3 = 125, 100^(1/3) is less than but closer to 125, so estimated value is 5 * 0.01 = 0.05.
To two significant digits, 100^(1/3) = 0.47.
Where some tickmarks would lie Log[10,2] = 0.3 or about 1/3 from the left
Log[10,3] = 0.48 or about 0.5
Log[10,4] = 0.60
Log[10,5] = 0.70
Log[10,6] = 0.78
Log[10,7] = 0.85
Log[10,8] = 0.90
Log[10,9] = 0.95

17. Main benefit: you are better able to understand many discussions, many journal articles, many seminars, related to biophysics
Other benefits:
Exposure to cultural style of thinking like a biophysicist: mix of measurement, estimation, simple models, important not to be too precise.
Knowledge of specific biophysical systems that have been studied experimentally and theoretically.
Technical skills: Taylor series without derivatives for approximation, random walks, Fourier method for solving differential equations, statistical physics, data on log-log plots, using Mathematica.
Answer is The green dot is about 2/3 of the way between 0.01 and 0.1 so the 0.01 value is multiplied by 10^(2/3) = 100^(1/3). Since 4^3 = 64 and 5^3 = 125, 100^(1/3) is less than but closer to 125, so estimated value is 5 * 0.01 = 0.05.
To two significant digits, 100^(1/3) = 0.47.
Where some tickmarks would lie Log[10,2] = 0.3 or about 1/3 from the left
Log[10,3] = 0.48 or about 0.5
Log[10,4] = 0.60
Log[10,5] = 0.70
Log[10,6] = 0.78
Log[10,7] = 0.85
Log[10,8] = 0.90
Log[10,9] = 0.95

18. Key physical ideas
Simple harmonic oscillator (small perturbations about equilibrium)
Ideal gas and ideal gas solutions (osmosis)
Statistical physics of multi-level systems
Random walks, entropy, macromolecular structure
Elasticity theory of 1d rods
Newtonian fluid mechanics and Navier-Stokes equations
Diffusion and random walks
Nonlinear dynamics of chemical kinetics, linear stability of uniformstates, pattern formation

19. Need to choose or adapt different models for different questions of same biophysical system

20. Different physical models for a protein

21. Different physical models for water

22. What topics have we not studied?
Biological networks: how to classify, dynamics
Brains: behavior from network of neurons
Bodies: differentiated multicellular organism from dynamics of a gene regulatory network
Disease caused by malfunctioning networks: depression and Alzheimer’s, cancer, aging
Ecologies: what determines number, kinds, interactions of species in given environment?
Quantum biology: photosynthesis, retina, electron transport.
Evolution: what is understood quantitatively and theoretically about speciation?
Origin of life, definition of life
Big data: how to extract insights from giant databases of genomics, epigenomics, proteomics, connectomics?

23. Best of luck next semester! Please stay in touch.

24. One-minute End-of-class Question