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A program for phosphorylation site assignment of LC-MS/MS data. It uses a linear-time and linear space dynamic programming strategy for phosphorylation site assignment. The algorithm optimizes the objective function defined as the summation of intensity peaks that are associated with theoretical peptide fragmentation ions. A classifier introduced in the algorithm exploits the specific characteristics of mass spectrometry data to distinguish between the correctly and incorrectly assigned site(s).
Scaffold PTM
Automates post-translational modification (PTM) site assignment in proteomic experiments. Scaffold PTM is a program assessing site assignments for any post-transnational modification (PTM). It accepts overlapping data from different peptides simultaneously to improve confidence in specific site assignments. It utilizes the Ascore algorithm to interpret sites of modification on a peptide-by-peptide basis. This tool permits users to study the peptide interpretations into protein specific sites of modification, comprised of multiple pieces of overlapping evidence.
INKA / Integrative Inferred Kinase Activity
Serves for phosphoproteomic inference of active phosphokinases. INKA utilizes label-free quantification of phosphopeptides derived from: kinases, kinase activation loops, kinase substrates deduced from prior experimental knowledge, and kinase substrates predicted from sequence motifs. This tool is able to identify active kinases, with potential clinical significance. It combines direct observations on phosphokinases, with observations on phosphoproteins that are known or predicted substrates for the pertinent kinase.
Turbo SLoMo
A software tool which can localise and score sites of protein modification in mass spectrometry data. Turbo SLoMo has been created to allow high throughput modification site localisation using the SLoMo algorithm. Turbo SLoMo takes input from pepxml formatted mass spectrometry search results and MS/MS spectra in the MGF format. Modifications of interest can be specified via the command line along with batch options allowing large datasets to be broken down into smaller sets when using a computational cluster.
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