The course will teach how MATLAB can be used to solve practical problems in data analysis that come from a wide range of disciplines such as biology, chemistry and physics. The first part of the course focuses on the foundations of Matlab programming:
- The Matlab working environment
- Variables, constants and reserved words
- Arrays and matrices
- Scripts
- The debugger
- Generating 2D and 3D Graphics
- Simple statistical analysis
- String manipulation
- Boolean logic and if statements
- Loops (while, for)
- Functions & Files
- Program design
- Matlab structures and tables
- Complexity
- Producing publication quality graphs
The second part of the course focuses on applying Matlab to practical problems in
data analysis:
- Mathematical modeling of cancer therapy using the Matlab ODE solvers
- Systems biology: protein production gene expression
- Analyzing images using the Matlab image processing toolbox
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SYLLABUS WEEK BY WEEK:
[1] Introduction
a. Why learn Matlab?
b. The Matlab working environment
c. The "help" command
d. Our first Matlab program.
[2] Basics
a. Variables, constants and reserved words
b. Arrays and matrices
c. Scripts
d. The debugger
[3] Graphics and simple analysis
a. 2D Graphics
b. simple statistical analysis (mean, std etc)
c. String manipulation
[4] Control
a. Boolean logic
b. If statements
[5] Loops
a. while
b. for
[6] Functions & Files
[7] Program design
a. Matlab structures and tables
b. Top down, bottom up, etc
c. Complexity
[8] Making simple Apps
[9] Matlab image unsupervised learning
[10] Matlab Supervised learning
[11] Solving differential equations numerically using Matlab
[12] & [13] Introduction of some advanced topics in how to prepare Graphs using Matlab:
a. Preparing publication-quality figures in Matlab
b. How to make Movies of data in Matlab
c. Tricks for extracting raw data from old published graphs
d. Advanced topics in 2-D and 3-D graphs: efficient ways of making graphs; more about Handle Graphics; Latex formatting of text embedded in graphs