The PepArML meta-search engine is open-for-business. New users can register for free, upload their spectra, submit large-scale meta-searches, monitor the search jobs, combine the completed searches using PepArML, and download the results, all via on-line PepArML meta-search engine site.
I’ll be presenting my ASMS 2009 poster “Improving the Sensitivity of Peptide Identification from Tandem Mass Spectra using Meta-Search, Grid-Computing, and Machine-Learning” on Wednesday, June 3, 10:30 – 2:30. This poster describes the use of, you guessed it, meta-search (many search engines via a single user-interface), grid-computing (lots of heterogeneous computers), and machine-learning (to reconcile the peptide identification results). The poster is available on the Edwards Lab publications page.
The PepArML unsupervised, model-free, machine-learning, peptide identification result combiner has been published in Clinical Proteomcis and is available via Springer’s Open Choice open access option.
N. Edwards, X. Wu, and C.-W. Tseng. “An Unsupervised, Model-Free, Machine-Learning Combiner for Peptide Identifications from Tandem Mass Spectra.” Clinical Proteomics 5.1 (2009). Final submitted manuscript.