PredictPA is a Bayesian network model that integrates genomic, transcriptomic and proteomic data to predict protein abundance. Specifically, by using expression, sequence and interaction data, we effectively link transcriptional information with post-transcriptional and protein translational data.
- Software is available here .
If you use PredictPA in your research, please cite the following paper:
Ahmed M. Mehdi, Ralph Patrick, Timothy L. Bailey and Mikael Boden (2014), " Predicting the Dynamics of Protein Abundance", Molecular and Cellular Proteomics. 13(5): 1330-1340. [Abstract and Full Text]