A enhancement to the popular peptide search engine X!Tandem is proposed, to allow it to run on new super-scalable MapReduce computer clusters. This will allow much faster and less-expensive operation, allowing proteomics researchers to routinely search for post-translational modifications (PTMs). Proteomics has led to many important advances in biological understanding. Yet, many valuable data sets are not searched for PTMs, simply because the computer power necessary to conduct the searches is not available. With this project, we plan to substantially reduce the computational cost of proteomics experiments, via a peptide search engine operating on highly-scalable computer clusters. The research team is well-qualified to undertake this research, having extensive, direct experience in all the scientific disciplines and specific software elements necessary. The research team includes experts in proteomics, mass spectrometry, peptide search, cloud computing, and MapReduce.
High-throughput analysis of post-translational modifications is increasingly pivotal for understanding the molecular function and dynamics of living cells. This proposal thus addresses key opportunities for applying proteomics to human health research.
| Pratt, Brian; Howbert, J Jeffry; Tasman, Natalie I et al. (2012) MR-Tandem: parallel X!Tandem using Hadoop MapReduce on Amazon Web Services. Bioinformatics 28:136-7 |
