Difference between revisions of "MAT5133"
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− | Mathematical Biology. | + | =Mathematical Biology - MAT4133/5133= |
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+ | The Mathematical Biology course is a broad introduction to nonlinear dynamics. Students are assumed to have an operative knowledge of single-variable calculus. Topics are introduced with interrelated biological examples of increasing difficulty. Students are exposed to discrete and continuous models. The mathematical content of the class includes: Flows on the line, linear stability analysis, matrix operations and eigenvalues, flows on the plane, bifurcations, discrete dynamical systems, and higher-dimensional systems. The biological problems studied include: Molecular processes (glycolysis, lactose operon, etc.), physiological processes (single neuron), and ecological processes (predator-prey, competing species, infectious disease modeling). | ||
+ | |||
+ | Suggested text(s) and/or readings: | ||
+ | * Open educational resources available in the Department of Mathematics for this course, available at https://mathresearch.utsa.edu/wiki | ||
+ | * Britton, Nick. Essential Mathematical Biology. Springer, 2005 (UMS Series). | ||
+ | * Fall, Chistopher P., Marland, Eric S., Wagner, John M., and Tyson, John J. (eds). Computational Cell Biology. Springer, 2002 (IAM Series). | ||
+ | * Keener, J. P., and James Sneyd. Mathematical physiology 1: Cellular physiology. New York, NY: Springer New York, 2009. | ||
+ | * Keener, James, and James Sneyd, eds. Mathematical physiology: II: Systems physiology. New York, NY: Springer New York, 2009. | ||
+ | * Strogatz, Steven H. Nonlinear Dynamics and Chaos. Westview Press, 2000. | ||
+ | |||
+ | {| class="wikitable" | ||
+ | ! Session !! Lecture !! Session !! Topics !! Book Section !! Competency Required. The student needs to know… !! Competency Gain. The student will learn to… !! Examples | ||
+ | |- | ||
+ | | 1 || || Introduction to Dynamical Systems. || Historical remarks. Concept of the qualitative analysis of a dynamical system. Linear vs. nonlinear problems. Examples from biology and physics. || Strogatz Chap. 1 || Single-variable calculus. || Define a dynamical system. Understand systems of equations. Provide general examples of dynamical systems in biology and physics. || Poincaré’s three-body problem. Lorentz’s system. Mandelbrot’s fractals. | ||
+ | |- | ||
+ | | 2 || L1 || Flows on the Line - Introduction || Simple example dx/dt = sin(x). || Strogatz 2.0, 2.1. || How to solve the separable differential equation dx/dt = sin(x) by integration. || Give a qualitative description of a simple dynamical system. || dx/dt = sin(x) | ||
+ | |- | ||
+ | | 3 || L2 || Fixed Points || Fixed points and stability. || Strogatz 2.2, 2.3. || Single-variable calculus. || Give a qualitative description of a simple dynamical system. || Population dynamics. Logistic equation of population growth | ||
+ | |- | ||
+ | | 4 || L3 || Linear Stability Analysis || Linearization about a fixed point. Existence and Uniqueness. || Strogatz 2.4, 2.5, 2.6. || Flows on the line. Taylor series. || Perform a linearization. Describe importance of fixed points. || No examples. Discuss homework | ||
+ | |- | ||
+ | | 5 || colspan="7"| HOMEWORK # 1 | ||
+ | |- | ||
+ | | 5 || L4 || Linear Stability Analysis || Linearization about a fixed point. Hyperbolic vs. non-hyperbolic fixed points. || Strogatz 2.4, 2.5, 2.6. || Flows on the line. Taylor series. || Perform a linearization. Describe importance of fixed points. || dx/dt = r-x^2 | ||
+ | |- | ||
+ | | 6 || L5 || Bifurcations || Saddle node bifurcation. Taylor expansions and normal forms. || Strogatz 3.0, 3.1. || Single-variable calculus. Taylor series. || Determine changes in a dynamical system with parameter variation. || dx/dt = r+x^2, dx/dt = r-x^2, dx/dt = r+x+e^x | ||
+ | |- | ||
+ | | 7 || L6 || Bifurcations || Transcritical bifurcation (supercritical, subcritical), pitchfork bifurcation. || Strogatz 3.2, 3.3, 3.4. || Single-variable calculus. Taylor series. || Determine changes in a dynamical system with parameter variation. Know how to eliminate dimensions of a system. Learn stability analysis of 1-D systems || dx/dt = rx-x^2, dx/dt = rx-x^3 | ||
+ | |- | ||
+ | | 8 || colspan="7"| COLLECT HOMEWORK # 1 | ||
+ | |- | ||
+ | | 8 || L6 || Dimensional analysis and scaling || Dimensionless groups. Buckingham’s Pi theorem. Stability of 1-D discrete systems in the context of the last problem in HW 1. || Murray 1.2, Strogatz 3.7. || Flows on the line. Bifurcations. || Make a dynamical system non-dimensional. || Population dynamics. Insect outbreak model: Spruce budworm. | ||
+ | |- | ||
+ | | 9 || L7 || Linear Systems || Introduction. Examples of two-dimensional linear systems. Lexicon. Eigenvalues and eigenvectors. || Strogatz 5.1. Class notes. || Single-variable calculus. How to solve the separable differential equation dx/dt = f(x) by integration. || Identify a linear system || Selected set of two examples that demonstrate stiff and non-stiff systems. | ||
+ | |- | ||
+ | | 10 || colspan="7"| PRACTICE TEST # 1 | ||
+ | |- | ||
+ | | colspan="8"| REVIEW SESSION | ||
+ | |- | ||
+ | | colspan="8"| RETURN HOMEWORK # 1 GRADED | ||
+ | |- | ||
+ | | 11 || L8 || Linear Systems || Eigenvalues and eigenvectors. Reduction of second order ODEs to a system of first order ODEs || Strogatz 5.1. Class notes. || Single-variable calculus. How to solve the separable differential equation dx/dt = f(x) by integration. || Identify a linear system || Selected set of two examples that demonstrate stiff and non-stiff systems. | ||
+ | |- | ||
+ | | 12 || L9 || Linear Systems || Classification of linear systems. Types of fixed points. Classification of fixed points. || Strogatz 5.2. Class notes. || Linear systems. || Classify linear systems. Identify and classify fixed points. || Continue use of selected examples. | ||
+ | |- | ||
+ | | 13 || colspan="7"| COLLECT HOMEWORK # 1 CORRECTIONS | ||
+ | |- | ||
+ | | colspan="8"| COLLECT PRACTICE TEST # 1 | ||
+ | |- | ||
+ | | colspan="8"| TEST # 1 | ||
+ | |- | ||
+ | | 14 || colspan="7"| SOLUTION TO TEST # 1 | ||
+ | |- | ||
+ | | colspan="8"| GIVE HOMEWORK # 2 | ||
+ | |- | ||
+ | | 15 || L10 || Two Dimensional Flows || Phase portrait. Consequences of the Hartman-Grossman theorem. Nullclines. Fixed points and linearization in two and more dimensions. Jacobian matrix. || Strogatz 6.1, 6.2. || Linear systems. || Read a phase portrait. || Selected examples. | ||
+ | |- | ||
+ | | 16 || L11 || Two Dimensional Flows || How eigenvalues determine repellers, attractors, saddles, centers, and fixed points. || Strogatz 6.3 || Linear systems. || Interpret a phase portrait based on eigenvalues. || Simple linear system. | ||
+ | |- | ||
+ | | 17 || L11 || Limit Cycles || Periodic motion. Poincaré-Bendixon Theorem. Introduction to limit cycles. Hopf bifurcation || Strogatz 4.0, 4.1, 6.3, 8.2. || Two dimensional flows. || Identify limit cycles. Determine existence of limit cycles. || Simple periodic system with a limit cycle. | ||
+ | |- | ||
+ | | 18 || L12 || Two Dimensional Flows || Applications in ecology. Population dynamics. Rabbit vs. sheep. || Strogatz 6.4. || Linear systems. || Interpret a phase portrait based on eigenvalues. || Species competition. Lokta-Volterra model of competition. | ||
+ | |- | ||
+ | | 19 || colspan="7"| COLLECT HOMEWORK # 2 | ||
+ | |- | ||
+ | | 19 || L13 || Limit Cycles || Applications in molecular biology. Glycolytic oscillations. || Strogatz 7.3, 7.5 || Two dimensional flows. || Describe qualitatively and quantitatively shape and period of closed orbits. || Cell biology: Glycolisis. Cell cycle. | ||
+ | |- | ||
+ | | 20 || L14 || Numerical Mathematics || Numerical solutions of ODEs || Kreyszig 19.1, Quarteroni, Sacco, Salieri 11.1, 11.8 || Linear algebra || Compute numerically a system of ODEs || None | ||
+ | |- | ||
+ | | 21 || colspan="7"| RETURN HOMEWORK # 2 GRADED | ||
+ | |- | ||
+ | | colspan="8"| ADVISE STUDENTS TO SEARCH FOR PAPERS FOR HW # 5 | ||
+ | |- | ||
+ | | colspan="8"| HAVE A BRIEF DISCUSSION ABOUT SCHOLAR DATABASES | ||
+ | |- | ||
+ | | 21 || L15 || Numerical Mathematics || Runge-Kutta 2nd order method || Kreyszig 19.3, Quarteroni et al. 11.9 || Linear algebra || Compute numerically a system of ODEs || None | ||
+ | |- | ||
+ | | 22 || L16 || Numerical Mathematics || Newton-Raphson method in two dimensions || Kreyszig 17.2 || Linear algebra || Compute numerically the steady states of a system of ODEs || Numerical roots of x^2 – x = 0 | ||
+ | |- | ||
+ | | 23 || L17 || Numerical Mathematics || Newton-Raphson method in multidimensions || Nash & Sofer 10.3, Quarteroni et al. 7.1 || Linear algebra || Compute numerically the steady states of a system of ODEs || Numerical roots of x^2 – x = 0 | ||
+ | |- | ||
+ | | 24 || colspan="7"| COLLECT HOMEWORK # 2 CORRECTIONS | ||
+ | |- | ||
+ | | colspan="8"| GIVE HOMEWORK # 3 | ||
+ | |- | ||
+ | | colspan="8"| INTRODUCTION TO COMPUTER SYSTEMS FOR NUMERICAL SOLUTIONS OF ODEs - XPP | ||
+ | |- | ||
+ | | 25 || colspan="7"| ADVISE STUDENTS TO SEARCH FOR PAPERS FOR HW # 5 | ||
+ | |- | ||
+ | | colspan="8"| PRACTICE TEST # 2 & REVIEW SESSION | ||
+ | |- | ||
+ | | 26 || L18 || Applied dynamical systems || Hodgkin-Huxley model. J. Physiology, 1952 || Fall et al. 2.1, 2.2, 2.5 || Dynamical systems, linear stability, bifurcations || Apply mathematical concepts to biological problems || Hodgkin-Huxley model of neural activity. | ||
+ | |- | ||
+ | | 27 || L19 || Applied dynamical systems || Fitzhugh-Nagumo model || Fall et al. 2.6, Strogatz problem 7.5.6 || Dynamical systems, linear stability, bifurcations || Apply mathematical concepts to biological problems || Fitzhugh-Nagumo model of neural activity. | ||
+ | |- | ||
+ | | 28 || colspan="7"| COLLECT PRACTICE TEST # 2 | ||
+ | |- | ||
+ | | colspan="8"| TEST # 2 | ||
+ | |- | ||
+ | | 29 || colspan="7"| SOLUTION TO TEST # 2 | ||
+ | |- | ||
+ | | 30 || L23 || Limit Cycles || Global bifurcations || Strogatz 8.4 || Dynamical systems, linear stability, bifurcations || Identify global bifurcations || Selected examples from the book | ||
+ | |- | ||
+ | | 31 || L20 || Stochastic Systems || Introduce the concept of PDF. Ion channels || Fall et al. 11.1 || Definition of probability || Apply stochastic concepts to dynamical systems || None | ||
+ | |- | ||
+ | | 32 || L20 || Stochastic Systems || Ion channels || Fall et al. 11.1 || Definition of probability || Apply stochastic concepts to dynamical systems || None | ||
+ | |- | ||
+ | | 33 || L21 || Stochastic Systems || Dwell times || Fall et al. 11.1 || Definition of probability || Apply stochastic concepts to dynamical systems || None | ||
+ | |- | ||
+ | | 34 || colspan="7"| COLLECT HOMEWORK # 3 | ||
+ | |- | ||
+ | | colspan="8"| GIVE HOMEWORK # 4 | ||
+ | |- | ||
+ | | 34 || L22 || Stochastic Systems || Ion channel ensemble || Fall et al. 11.1 || Definition of probability || Apply stochastic concepts to dynamical systems || None | ||
+ | |- | ||
+ | | 35 || L24 || Quasi-equilibrium || Michelis-Menten kinetics || Fall et al. 4.7 || Dynamical systems, linear stability, bifurcations || Identify functional responses || Bacterial glucose binding | ||
+ | |- | ||
+ | | 36 || colspan="7"| RETURN HOMEWORK # 3 GRADED | ||
+ | |- | ||
+ | | 36 || L25 || Chaos || Intro, definitions || Strogatz 9.2, 9.4 || Two dimensional flows. || Understand the concept of chaos. || Lorenz equations. | ||
+ | |- | ||
+ | | 37 || L26 || Power-laws || Intro, definitions || PPT || Chaos || Identify when a power law is at play || None | ||
+ | |- | ||
+ | | 38 || colspan="7"| COLLECT HOMEWORK # 3 CORRECTIONS | ||
+ | |- | ||
+ | | 38 || L27 || One-dimensional maps || Introduction. Fixed points and cobwebs. || Strogatz 10.0, 10.1, 10.2, 10.3 || Flows on the line. || Produce and analyze a one-dimensional map. || Population dynamics: Logistic map. | ||
+ | |- | ||
+ | | 39 || colspan="7"| COLLECT HOMEWORK # 4. | ||
+ | |- | ||
+ | | colspan="8"| GIVE HOMEWORK # 5. | ||
+ | |- | ||
+ | | 39 || L28 || One-dimensional maps || Age-structured populations in space time. Leslie matrices. || Britton 1.9 || One-dimensional maps || Understand age-structured discrete models. || Physiology: Red blood cell count. | ||
+ | |- | ||
+ | | 40 || colspan="7"| PRACTICE FINAL & FULL REVIEW SESSION | ||
+ | |- | ||
+ | | 41 || colspan="7"| PRACTICE FINAL & FULL REVIEW SESSION | ||
+ | |- | ||
+ | | colspan="8" | RETURN HOMEWORK #4 | ||
+ | |} |
Revision as of 08:17, 24 March 2023
Mathematical Biology - MAT4133/5133
The Mathematical Biology course is a broad introduction to nonlinear dynamics. Students are assumed to have an operative knowledge of single-variable calculus. Topics are introduced with interrelated biological examples of increasing difficulty. Students are exposed to discrete and continuous models. The mathematical content of the class includes: Flows on the line, linear stability analysis, matrix operations and eigenvalues, flows on the plane, bifurcations, discrete dynamical systems, and higher-dimensional systems. The biological problems studied include: Molecular processes (glycolysis, lactose operon, etc.), physiological processes (single neuron), and ecological processes (predator-prey, competing species, infectious disease modeling).
Suggested text(s) and/or readings:
- Open educational resources available in the Department of Mathematics for this course, available at https://mathresearch.utsa.edu/wiki
- Britton, Nick. Essential Mathematical Biology. Springer, 2005 (UMS Series).
- Fall, Chistopher P., Marland, Eric S., Wagner, John M., and Tyson, John J. (eds). Computational Cell Biology. Springer, 2002 (IAM Series).
- Keener, J. P., and James Sneyd. Mathematical physiology 1: Cellular physiology. New York, NY: Springer New York, 2009.
- Keener, James, and James Sneyd, eds. Mathematical physiology: II: Systems physiology. New York, NY: Springer New York, 2009.
- Strogatz, Steven H. Nonlinear Dynamics and Chaos. Westview Press, 2000.
Session | Lecture | Session | Topics | Book Section | Competency Required. The student needs to know… | Competency Gain. The student will learn to… | Examples |
---|---|---|---|---|---|---|---|
1 | Introduction to Dynamical Systems. | Historical remarks. Concept of the qualitative analysis of a dynamical system. Linear vs. nonlinear problems. Examples from biology and physics. | Strogatz Chap. 1 | Single-variable calculus. | Define a dynamical system. Understand systems of equations. Provide general examples of dynamical systems in biology and physics. | Poincaré’s three-body problem. Lorentz’s system. Mandelbrot’s fractals. | |
2 | L1 | Flows on the Line - Introduction | Simple example dx/dt = sin(x). | Strogatz 2.0, 2.1. | How to solve the separable differential equation dx/dt = sin(x) by integration. | Give a qualitative description of a simple dynamical system. | dx/dt = sin(x) |
3 | L2 | Fixed Points | Fixed points and stability. | Strogatz 2.2, 2.3. | Single-variable calculus. | Give a qualitative description of a simple dynamical system. | Population dynamics. Logistic equation of population growth |
4 | L3 | Linear Stability Analysis | Linearization about a fixed point. Existence and Uniqueness. | Strogatz 2.4, 2.5, 2.6. | Flows on the line. Taylor series. | Perform a linearization. Describe importance of fixed points. | No examples. Discuss homework |
5 | HOMEWORK # 1 | ||||||
5 | L4 | Linear Stability Analysis | Linearization about a fixed point. Hyperbolic vs. non-hyperbolic fixed points. | Strogatz 2.4, 2.5, 2.6. | Flows on the line. Taylor series. | Perform a linearization. Describe importance of fixed points. | dx/dt = r-x^2 |
6 | L5 | Bifurcations | Saddle node bifurcation. Taylor expansions and normal forms. | Strogatz 3.0, 3.1. | Single-variable calculus. Taylor series. | Determine changes in a dynamical system with parameter variation. | dx/dt = r+x^2, dx/dt = r-x^2, dx/dt = r+x+e^x |
7 | L6 | Bifurcations | Transcritical bifurcation (supercritical, subcritical), pitchfork bifurcation. | Strogatz 3.2, 3.3, 3.4. | Single-variable calculus. Taylor series. | Determine changes in a dynamical system with parameter variation. Know how to eliminate dimensions of a system. Learn stability analysis of 1-D systems | dx/dt = rx-x^2, dx/dt = rx-x^3 |
8 | COLLECT HOMEWORK # 1 | ||||||
8 | L6 | Dimensional analysis and scaling | Dimensionless groups. Buckingham’s Pi theorem. Stability of 1-D discrete systems in the context of the last problem in HW 1. | Murray 1.2, Strogatz 3.7. | Flows on the line. Bifurcations. | Make a dynamical system non-dimensional. | Population dynamics. Insect outbreak model: Spruce budworm. |
9 | L7 | Linear Systems | Introduction. Examples of two-dimensional linear systems. Lexicon. Eigenvalues and eigenvectors. | Strogatz 5.1. Class notes. | Single-variable calculus. How to solve the separable differential equation dx/dt = f(x) by integration. | Identify a linear system | Selected set of two examples that demonstrate stiff and non-stiff systems. |
10 | PRACTICE TEST # 1 | ||||||
REVIEW SESSION | |||||||
RETURN HOMEWORK # 1 GRADED | |||||||
11 | L8 | Linear Systems | Eigenvalues and eigenvectors. Reduction of second order ODEs to a system of first order ODEs | Strogatz 5.1. Class notes. | Single-variable calculus. How to solve the separable differential equation dx/dt = f(x) by integration. | Identify a linear system | Selected set of two examples that demonstrate stiff and non-stiff systems. |
12 | L9 | Linear Systems | Classification of linear systems. Types of fixed points. Classification of fixed points. | Strogatz 5.2. Class notes. | Linear systems. | Classify linear systems. Identify and classify fixed points. | Continue use of selected examples. |
13 | COLLECT HOMEWORK # 1 CORRECTIONS | ||||||
COLLECT PRACTICE TEST # 1 | |||||||
TEST # 1 | |||||||
14 | SOLUTION TO TEST # 1 | ||||||
GIVE HOMEWORK # 2 | |||||||
15 | L10 | Two Dimensional Flows | Phase portrait. Consequences of the Hartman-Grossman theorem. Nullclines. Fixed points and linearization in two and more dimensions. Jacobian matrix. | Strogatz 6.1, 6.2. | Linear systems. | Read a phase portrait. | Selected examples. |
16 | L11 | Two Dimensional Flows | How eigenvalues determine repellers, attractors, saddles, centers, and fixed points. | Strogatz 6.3 | Linear systems. | Interpret a phase portrait based on eigenvalues. | Simple linear system. |
17 | L11 | Limit Cycles | Periodic motion. Poincaré-Bendixon Theorem. Introduction to limit cycles. Hopf bifurcation | Strogatz 4.0, 4.1, 6.3, 8.2. | Two dimensional flows. | Identify limit cycles. Determine existence of limit cycles. | Simple periodic system with a limit cycle. |
18 | L12 | Two Dimensional Flows | Applications in ecology. Population dynamics. Rabbit vs. sheep. | Strogatz 6.4. | Linear systems. | Interpret a phase portrait based on eigenvalues. | Species competition. Lokta-Volterra model of competition. |
19 | COLLECT HOMEWORK # 2 | ||||||
19 | L13 | Limit Cycles | Applications in molecular biology. Glycolytic oscillations. | Strogatz 7.3, 7.5 | Two dimensional flows. | Describe qualitatively and quantitatively shape and period of closed orbits. | Cell biology: Glycolisis. Cell cycle. |
20 | L14 | Numerical Mathematics | Numerical solutions of ODEs | Kreyszig 19.1, Quarteroni, Sacco, Salieri 11.1, 11.8 | Linear algebra | Compute numerically a system of ODEs | None |
21 | RETURN HOMEWORK # 2 GRADED | ||||||
ADVISE STUDENTS TO SEARCH FOR PAPERS FOR HW # 5 | |||||||
HAVE A BRIEF DISCUSSION ABOUT SCHOLAR DATABASES | |||||||
21 | L15 | Numerical Mathematics | Runge-Kutta 2nd order method | Kreyszig 19.3, Quarteroni et al. 11.9 | Linear algebra | Compute numerically a system of ODEs | None |
22 | L16 | Numerical Mathematics | Newton-Raphson method in two dimensions | Kreyszig 17.2 | Linear algebra | Compute numerically the steady states of a system of ODEs | Numerical roots of x^2 – x = 0 |
23 | L17 | Numerical Mathematics | Newton-Raphson method in multidimensions | Nash & Sofer 10.3, Quarteroni et al. 7.1 | Linear algebra | Compute numerically the steady states of a system of ODEs | Numerical roots of x^2 – x = 0 |
24 | COLLECT HOMEWORK # 2 CORRECTIONS | ||||||
GIVE HOMEWORK # 3 | |||||||
INTRODUCTION TO COMPUTER SYSTEMS FOR NUMERICAL SOLUTIONS OF ODEs - XPP | |||||||
25 | ADVISE STUDENTS TO SEARCH FOR PAPERS FOR HW # 5 | ||||||
PRACTICE TEST # 2 & REVIEW SESSION | |||||||
26 | L18 | Applied dynamical systems | Hodgkin-Huxley model. J. Physiology, 1952 | Fall et al. 2.1, 2.2, 2.5 | Dynamical systems, linear stability, bifurcations | Apply mathematical concepts to biological problems | Hodgkin-Huxley model of neural activity. |
27 | L19 | Applied dynamical systems | Fitzhugh-Nagumo model | Fall et al. 2.6, Strogatz problem 7.5.6 | Dynamical systems, linear stability, bifurcations | Apply mathematical concepts to biological problems | Fitzhugh-Nagumo model of neural activity. |
28 | COLLECT PRACTICE TEST # 2 | ||||||
TEST # 2 | |||||||
29 | SOLUTION TO TEST # 2 | ||||||
30 | L23 | Limit Cycles | Global bifurcations | Strogatz 8.4 | Dynamical systems, linear stability, bifurcations | Identify global bifurcations | Selected examples from the book |
31 | L20 | Stochastic Systems | Introduce the concept of PDF. Ion channels | Fall et al. 11.1 | Definition of probability | Apply stochastic concepts to dynamical systems | None |
32 | L20 | Stochastic Systems | Ion channels | Fall et al. 11.1 | Definition of probability | Apply stochastic concepts to dynamical systems | None |
33 | L21 | Stochastic Systems | Dwell times | Fall et al. 11.1 | Definition of probability | Apply stochastic concepts to dynamical systems | None |
34 | COLLECT HOMEWORK # 3 | ||||||
GIVE HOMEWORK # 4 | |||||||
34 | L22 | Stochastic Systems | Ion channel ensemble | Fall et al. 11.1 | Definition of probability | Apply stochastic concepts to dynamical systems | None |
35 | L24 | Quasi-equilibrium | Michelis-Menten kinetics | Fall et al. 4.7 | Dynamical systems, linear stability, bifurcations | Identify functional responses | Bacterial glucose binding |
36 | RETURN HOMEWORK # 3 GRADED | ||||||
36 | L25 | Chaos | Intro, definitions | Strogatz 9.2, 9.4 | Two dimensional flows. | Understand the concept of chaos. | Lorenz equations. |
37 | L26 | Power-laws | Intro, definitions | PPT | Chaos | Identify when a power law is at play | None |
38 | COLLECT HOMEWORK # 3 CORRECTIONS | ||||||
38 | L27 | One-dimensional maps | Introduction. Fixed points and cobwebs. | Strogatz 10.0, 10.1, 10.2, 10.3 | Flows on the line. | Produce and analyze a one-dimensional map. | Population dynamics: Logistic map. |
39 | COLLECT HOMEWORK # 4. | ||||||
GIVE HOMEWORK # 5. | |||||||
39 | L28 | One-dimensional maps | Age-structured populations in space time. Leslie matrices. | Britton 1.9 | One-dimensional maps | Understand age-structured discrete models. | Physiology: Red blood cell count. |
40 | PRACTICE FINAL & FULL REVIEW SESSION | ||||||
41 | PRACTICE FINAL & FULL REVIEW SESSION | ||||||
RETURN HOMEWORK #4 |