Murphy Lab

 Cytometry Development Workshop

 Flow Cytometry



 Carnegie Mellon University
 Computational Biology Department
 Center for Bioimage Informatics
 Biological Sciences Department
 Biomedical Engineering Department
 Machine Learning Department

Murphy Lab - Software

The data and software used for the following paper can be downloaded below:

T. Zhao and R.F. Murphy. (2007) Automated learning of generative models for subcellular location: Building blocks for systems biology. Cytometry 71A:978-990.
The data and code are contained in five .tgz files (gzipped tar archives):

If you would like to regenerate all results from scratch, download and untar just the code and raw data and run ml_gendataall.m - this will take over a week on a single 1.7 GHz processor. It will generate the files that are in genmodel_procdataonly.tgz. Figures and tables in the paper can then be generated by running paperresults.m

If you would just like to regenerate the figures from the processed results, download and untar the first three .tgz files and run paperresults.m

If you would just like to generate images from the trained models described in the paper, download just the first and last files (codeonly and modelsonly) and run ml_testgenimg. The file can be modified to specify which models you wish to generate images from. Many examples of generated images can be found here. If you would just like to view the synthesized images used in the paper, download just the synimagesonly file.

System requirements

The scripts were written for Matlab on Linux, version 7.0 or above. The statistics toolbox, image processing toolbox, splines toolbox and optimization toolbox for Matlab are also required.

Tools created by others that are included in the code distribution for convenience

Last Updated: 16 Sep 2011

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