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Published in Bioinformatics, 24:1652-3, 2008.

Download the Paper (417 K, PDF file) - June 1, 2008 Tell a colleague about it. Printing Tips: Select 'print as image' in the Acrobat print dialog if you have trouble printing.

ABSTRACT:
In a recent article in this journal, Khatun, Hamlett, and Giddings (2008) (KHG) advance a new scoring scheme for use in conjunction with tandem mass spectrometry (MS/MS) based peptide identification. As they note, such identifications are fundamental to much proteomics research but, due to MS/MS data complexity and the scale of attendant database searches, their accuracy is limited. The scoring technique they propose, which employs a hidden Markov model (HMM) over a set of states that represent key features of MS/MS data, is convincingly motivated and exhibits good performance. The purpose of this brief note is to critique the method chosen for calibrating the HMM scores, rather than the genesis of the scores themselves.

SUGGESTED CITATION:
Mark R. Segal, "On E-values for Tandem MS Scoring Schemes" (June 1, 2008). Center for Bioinformatics & Molecular Biostatistics. Paper e-values-ms.
http://repositories.cdlib.org/cbmb/e-values-ms