# Welcome to the webpage of  Peter Nagy

### Experience and experiments with Matlab...

"What a 'user-friendly' application!" This was my first impression when I first installed Matlab on my computer and it started up with screen with a command prompt and basically nothing else. But I gradually began to appreciate the flexibility and power of data analysis and the relative ease of programming of Matlab. I wrote Matlab code for fun and for developing applications for myself or my PhD students. Below I give you a selection of the utilities I developed.

### regressContourPlot

You can fit a linear regression line on 2D histogram data, i.e. if you already don't have the original data set containing two measurements for each data point.

Syntax:[r,slope,intercept]=regressContourPlot(twoDHist,xScale,yScale)

Help is available by typing "help regressContourPlot" at the Matlab command prompt.

### createTrend

A trend line can be created from a data set containing two measurements for each data point. In order to create a trend line the X range is divided into the given number of bins and the mean of the Y variable in each bin is calculated.

Syntax: createTrend(XYData) or [trendline,binsX. freq]= createTrend(XYData,XMin,XMax,NumBins)

Help is available by typing "help createTrend" at the Matlab command prompt.

### createContour

You can generate a 2D histogram (contour plot) interactively from a set of data containing two measurements for each data point.

Syntax: createContour(XYData)

Help is available by typing "help createContour" at the Matlab command prompt.

### Fitting the Hill equation to data points: fithill

The program fits the Hill equation to measurement data. The Hill equation has the following forms depending on whether IC50 or EC50 is fitted on concentrations on a linear or logarithmic scale:

The program can be run in GUI mode or command-prompt mode.

• GUI mode: In order to run the program in GUI mode start it without input arguments, i.e. type "fithill" at the Matlab command prompt.
• command prompt mode:[fittedParameters,rsquared]=fithill(xdata,ydata,PropName,PropVal1,PropVal2,...) OR [fittedParameters,rsquared,fittedN]=fithill(xdata,ydata,PropName,PropVal1,ProbVal2,...)
Output argument 'fittedN' is required if propName 'logconctoplot' is given among the arguments.

xdata = LOG10 of the drug concentrations (LOG10!!!!!!!)
ydata = cell numbers or absorbances
fittedParameters = structure with the following fields:
fittedParameters.min
fittedParameters.max
fittedParameters.kd
fittedParameters.n
fittedParameters.minCI
fittedParameters.maxCI
fittedParameters.kdCI
fittedParameters.nCI

rsquared = goodness of fit
fittedN = calculated curve using the best fit parameters at the concentrations given in the argument list after 'logconctoplot'

The following parameters are followed by two numbers:
 Parameter name Parameter value 1 Parameter value 2 ic50 1=to fit, 0=fixed parameter if first parameter is 1 -> initial valueif first parameter is 0 -> value of the fixed parameter ec50 same as above same as above n same as above same as above min same as above same as above max same as above same as above

If 'ec50' and 'ic50' is not followed by a numeric parameter, it only specifies whether a decreasing or increasing curve is to be fitted.

The following parameters are followed by one number or variable:
confint- confidence bounds will be calculated at the % level specified by the number following 'confint'
logconctoplot - LOG10concentrations (!!!!) at which fittedN will be calculated using the fit parameters

The following parameters aren't followed by anything.
ver - version of the program
version - same as above

help - displays this help