Continuous Profile Models (CPM) Matlab Toolbox
Written by Jennifer Listgarten

Summary: This toolbox provides Matlab implementations of Continuous Profile Models (CPM) for alignment and normalization of time series data. Specifically, two models are provided (well, one so far), the EM-CPM, from the paper "Multiple Alignment of Continuous Time Series", and the HB-CPM, from the paper "Bayesian Detection of Infrequent Differences in Sets of Time Series with Shared Structure". The HB-CPM implementation is not yet available. Both of these models are reported in my PhD thesis, which is listed along with other references, below.

Conditions of Use: This toolbox is available free for educational and research use. All use of this software is at the user's own risk. Please cite my thesis if using this toolbox. Also, as time has gone on, the dependencies have caused the toolbox to require tweaks, etc. which I have not done myself. If you have gotten the toolbox to work, could you please send me a note (jennl [at] microsoft.com) on what you had to do to get it working so that I can help others?

Download the Toolbox



• Before downloading the toolbox, you may want to read the README file, which contains some information about using the CPM Matlab toolbox. You will also need to read relevant portions of the literature below to understand the toolbox.
  
  
• If after reading the README above, you want to download the code package, then grab this file (which includes Matlab code and demo scripts). The data which goes with the demo scripts can be found separately (because of the large size), here. There is a data README file in that directory explaining the various data sets.
  
  
• To keep track of code updates and bug reports/fixes, see CPM Toolbox News.
  
  

  References

• Analysis of sibling time series data: alignment and difference detection. (abstract and thesis)
  Jennifer Listgarten,
  Ph.D. Thesis, Department of Computer Science, University of Toronto, 2006.
  
  
• Multiple Alignment of Continuous Time Series. (abstract, paper, slides, and audio demo)
  Jennifer Listgarten, Radford M. Neal, Sam T. Roweis and Andrew Emili,
  in Advances in Neural Information Processing Systems 17, MIT Press, Cambridge, MA, 2005 (NIPS 2004).
  
  
• Bayesian Detection of Infrequent Differences in Sets of Time Series with Shared Structure. (abstract, paper)
  Jennifer Listgarten, Radford M. Neal, Sam T. Roweis, Rachel Puckrin and Sean Cutler,
  To appear in Advances in Neural Information Processing Systems 19, MIT Press, Cambridge, MA, 2007 (NIPS 2006).
  Best Student Paper, Honorable Mention
  
  
• Difference detection in LC-MS data for protein biomarker discovery. (abstract, paper and data set)
  Jennifer Listgarten, Radford M. Neal, Sam T. Roweis, Peter Wong and Andrew Emili,
  In Bioinformatics, 2007, 23:e198-e204 [by way of ECCB 2006 (European Conference on Computational Biology)]
  Best Student Paper, 3rd prize
  
  
• Statistical and computational methods for comparative proteomic profiling using liquid chromatography-tandem mass spectrometry. (abstract) (paper)
  Jennifer Listgarten and Andrew Emili,
  in Molecular and Cellular Proteomics, 2005 4:419-434.
  
  
  

  CPM Toolbox News
  
  

• October 12th, 2006 -- First version released. This contains an implementation of the EM-CPM, along with scripts which show how to use it, and some demo data that can be used with the scripts. The HB-CPM is not yet ready.
  
  
  
  
  
  
  
  
  
  
  
  
  
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