compendium

C. Jackson, E. Glory-Afshar, R. F. Murphy and J. Kovačević. Model building and intelligent acquisition with application to protein subcellular location classification. Bioinformatics, 27(13):1854-1859, May 2011.

[pdf | @ Bioinformatics website | bibtex]

We present a framework and algorithms to intelligently acquire movies of protein subcellular location patterns by learning their models as they are being acquired, and simultaneously determining how many cells to acquire, as well as how many frames to acquire per cell. This is motivated by the desire to minimize acquisition time and photobleaching, given the need to build such models for all proteins, in all cell types, under all conditions. Our key innovation is to build models during acquisition rather than as a post-processing step, thus allowing us to intelligently and automatically adapt the acquisition process given the model acquired.

We validate our framework on protein subcellular location classification, and show that the combination of model building and intelligent acquisition results in time and storage savings without loss of classification accuracy, or, alternatively, higher classification accuracy for the same total acquisition time.

We performed our experiments on a collection of 3D movies of GFP-tagged proteins in NIH 3T3 cells over 12 different cell lines, with a different protein labeled in each cell line. At each time point of the movie we have a single channel stack of 15 z-slices, 1280x1024 pixels each. The x,y-resolution is 0.11 microns, and the distance between pixels in the z-direction is 0.5 microns. There is a 45 second interval between frames. To inquire about obtaining a copy of this data set, please contact murphy at cmu dot edu.

matlab

The zipped archive contains the readme file as well as the code to generate the results in the paper.

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This work is licensed under a Creative Commons GNU General Public License. To view a copy of this license, visit http://creativecommons.org/licenses/GPL/2.0. If you use this code or any part thereof in your research or publication, please also include a reference to this paper. Thank you!

MATLAB 2007a on Windows XP Professional, SP2

MATLAB 2009b on Windows 7

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