Template:Virtual Cell Exercises

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(Relevance of FRAP to courses)
(Relevance of FRAP to courses)
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Data Set: The first postbleach image is at 0 time ( t=0).  For each set of data (i=1,..,4), we give the number of microns squared in the bleach region (msqi), and the average pre-bleach fluorescence within the same region.  [Fi(-)].   
Data Set: The first postbleach image is at 0 time ( t=0).  For each set of data (i=1,..,4), we give the number of microns squared in the bleach region (msqi), and the average pre-bleach fluorescence within the same region.  [Fi(-)].   
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'''(See print out for equations)''' 
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[[media:FiINaROI.jpg]]
To normalize data across images      vs.    (t/msqi)
To normalize data across images      vs.    (t/msqi)

Revision as of 18:25, 20 December 2007

This exercise draws on a Virtual Cell Tutorial that can be found at the Virtual Cell website [1]

The first tutorial is based on FRAP. We use the FRAP Tutorial to become with the Virtual Cell user interface and commands.

Relevance of FRAP to courses

Course Relevance: Cell Biology, Biochemistry

Concepts

  • Biology: diffusion, compartments
  • Experiments: time series, fluorescent microscopy, wave lengths, lasers
  • Data Analysis: image capture, image analysis

Experimental principle: Fluorescence Recovery After Photobleaching (FRAP) is a fluorescent optical technique used to measure the dynamics of a population of molecules over time and chemical changes of molecular species. The fluorescently labeled molecules are visualized through an epifluorescent or confocal microscope using low light excitation. The excitation light is focused onto a small region of molecules and pulsed to a high intensity in order to photobleach the fluorophore within the illuminated region. A blackened area of photobleached molecules surrounded by fluorescently labeled molecules that are not photobleached will result from the high intensity light. The molecules that are not photobleached will diffuse, providing they can, into this region. The blackened area will gradually increase in intensity (recover) over time as the molecules diffuse.

Basic learning goals (BLG):

  • To have students do data analysis
  • To become familiar with constructing a simple model in Virtual Cell.

Advanced learning goals (ALG):

  • extract data values from image files
  • compare experimental data to multiple biological, computational models i.e. free diffusion, diffusion with binding, immobile fractions, etc.

Materials Needed:

ALG: Image stack, image analysis data To obtain image stack in lab the following are needed:

-Fluorescent microscope -fluorescent probe -labeled cell -camera -image capture and analysis software (e.g. ImageJ).


Image stack for extracting values using Image J:

  • Download and unzip image stack (Coming Soon).
    • Images are essentially wide field fluorescent images. They were collected with an open pin hole on confocal microscope.
  • Image analysis:
    • Use image analysis software to extract pixel values for fluoresence intensity


BLG: Download excel spreadsheet of fluorescent intensity data (available post workshop).

Data Set: The first postbleach image is at 0 time ( t=0). For each set of data (i=1,..,4), we give the number of microns squared in the bleach region (msqi), and the average pre-bleach fluorescence within the same region. [Fi(-)].

media:FiINaROI.jpg

To normalize data across images vs. (t/msqi)

Tasks: 1. In excel, plot the data as a time series. To compare the plots, normalize based on t/msqi.

2. Compare results to Virtual Cell FRAP simulation What is needed in the simulation for an accurate comparison to experiment?

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