| PROPA home | Download | Inputs | Outputs | Examples |
| Description: This software implements the MCMC and Monte Carlo variational methods to fit, analyse, summarise and use the Bayesian models for Probabilistic Pathway Annotation in genomics, detailed in Shen & West, 2009.
Acknowledgements: The research and development underlying the code provided here was supported, in part, by the National Science Foundation (grants DMS-0102227 and DMS-0342172) and the National Institutes of Health (grant NCI U54-CA-112952-01). Any opinions, findings and conclusions or recommendations expressed in this work are those of the authors and do not necessarily reflect the views of the NSF or NIH. Disclaimer: This software is made freely available to any interested user. The authors can provide no support nor assistance with implementations beyond the details and examples here, nor extensions of the code for other purposes. The download has been tested to confirm all details are operational as described here. It is understood by the user that neither the authors nor Duke University bear any responsibility nor assume any liability for any end-use of this software. It is expected that appropriate credit/acknowledgement be given should the software be included as an element in other software development or in publications. PROPA developed by: Haige Shen & Quanli Wang
|