Basics of
Programming (Thurs. / Fri.; Springer)
- Reading a line of code
- Variables – x=2
- Entering
- Retrieving
- Mathematical Operations + - * / ^
- Order of Operations
- Arrays
- Loading
- Visualizing
- Retrieving Values
- Altering Values
- Basic Functions – Analyzing a dataset
- Length, size
- Mean, median, standard deviation
- Sort
- Functions of 2D arrays
- Entering Arrays
- Bracket operator
- Colon operator
- Comma semicolon
- Conditional Retrieval
- Ploting
- 2D: colors, lines, labels
- 3D
- Scripts
- Conditional States and Control Flow
- For loops
- If, Elseif, Else
- !, ==, >, <, >=
- Or and And (| || & &&)
- While
- Counters
- Cell Arrays
- Entering
- Retrieving
- fieldnames
- Function
- Data Structures
- Strings – dealing with text and mixed data
- Parsing data
Statistics with MATLAB
(Monday, AM; Born)
- Rattus binomialis: When is he guessing?
- all you need is 'rand'
- simulations and probability
- 'for' loops
- tricky indexing into arrays
- 'tic' and 'toc' to time code execution
- binomial distribution
- pdf's and cdf's
- Bootstrap
Bill: Statistics for the common man
- operations along columns of 2D matrix
- use of 'repmat'
- simple descriptive statistics: mean, median,
standard error
- plotting functions: 'plot', 'errorbar',
'polar'
- handle graphics
- bootstrapping: null hypothesis; permutation test;
confidence intervals
- Sorting
spikes: The joys of dimensionality reduction
- thresholding to find peaks in data
- using 'diff' to find events in continuous data
- PCA/SVD to reduce dimensionality of data
- 3D plotting
- ISI histograms
Image
Processing I: Computer Processing
(Monday, PM; Springer)
- Visualizing an image in MATLAB
- loading images – imread and dragging
- displaying images –imshow, imagesc, surf
- data types – double, mat2gray
- Manipulating Pixels
- Background Subtraction
- Rescaling
- Transform – e.g. log
- Manipulating Field of pixels – Filters
- Intensity Preserving
- Non-Intensity Preserving
- Contrast
- Vertical Lines
- Horizontal Lines
- Edges
- Contrast – Laplacian
- Laplacian of Gaussian (LoG)
Image Processing II: Images and Your Brain (Tuesday, AM; Born)
- Horace Barlow: Image Statistics and "Suspicious
Coincidences"
- loading and displaying images
- histograms and probability density functions
- nearby pixels are similar: correlation with
'corrcoef'
- center-surround: LoG and 'imfilter'
- orientation selectivity: finding
"suspicious coincidences with 'colfilt'
- David Marr: Where's
Abe?
- image manipulation: blkproc
- edge detection: LoG and thresholding
- image filtering in the frequency domain:
'fft2', 'ifft2'
- band-rejection filters
- zero-crossings and the "raw primal
sketch"
- better recognition through subtraction
Image Processing III: Segmentation
- Finding cells or features
- Thresholding
- Bwlabel
- Cleaning up the features – imopen, imclose,
imerode imdialate
- Quantitating Cell
- Regionprops
- Extracting values from pixels
Modeling with SIMBIOLOGY
(Tuesday, PM; Springer)
- Launching simulink
- The hydrogen model – mRNA synthesis and decay
- Drawing a model
- Setting the rate equations
- Running a simulation
- Running a parameter scan
- Extract the data into MATLAB to manipulate
- Models
- Enzymatic reactions
- Binding unbinding reaction
- Ligand Receptor with Sink/Drug pharmacology
with Sink
- Competitive Inhibition
- Multisite Phosphorylation