The STEPP software contains an implementation of a trained SVM (Support Vector Machine) that can compute a score representing how "proteotypic" a peptide is by LC-MS. The program can read a protein file, perform an in-silico digestion, and compute the observability score for each tryptic or partially tryptic peptide. Note that larger (positive) scores mean a peptide is predicted to be more proteotypic while lower (negative) scores mean the peptide is not predicted to be proteotypic.

The SVM model used by STEPP is a simple descriptor space based on 35 properties of amino acid content, charge, hydrophilicity, and polarity for the quantitative prediction of proteotypic peptides. The model was trained and validated with three independently derived AMT databases (Shewanella oneidensis, Salmonella typhimurium, Yersinia pestis). The SVM resulted in an average accuracy measure of ~0.8 with a standard deviation of less than 0.025.

This software requires that the Java 6 Runtime be installed prior to use. You can download the standard edition of Java from Java.com

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Version	v1.1	Requirements	Java Runtime Environment, v1.5
Date Updated	March 31, 2008	File Size (Software Tool)	2.4 MB (ZIP)
Registration Required	No	File size (Source Code)	n/a
Developers	Bobbie-Jo Webb-Robertson and Anuj Shah
Comments	See the complete Revision History for a history of changes

Acknowledgment

All publications that utilize this software should provide appropriate acknowledgement to PNNL and the OMICS.PNL.GOV website. However, if the software is extended or modified, then any subsequent publications should include a more extensive statement, using this text or a similar variant:

This work was supported through the Laboratory Directed Research and Development at Pacific Northwest National Laboratory (PNNL) and the U.S. Department of Energy (DOE) Office of Advanced Scientific Computing Research under contract No. 47901. PNNL is a multiprogram national laboratory operated by Battelle for the U.S. DOE under contract DE-AC06-76L01830.