HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Full Text Full Text (PDF) Supplemental Data All Versions of this Article: T600050-MCP200v1 6/9/1638    most recent Submit a response Alert me when this article is cited Alert me when eLetters are posted Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Request Permissions Glossary Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Shilov, I. V. Articles by Schaeffer, D. A. Search for Related Content PubMed PubMed Citation Articles by Shilov, I. V. Articles by Schaeffer, D. A. Social Bookmarking                      What's this?

Molecular & Cellular Proteomics 6:1638-1655, 2007.
© 2007 by The American Society for Biochemistry and Molecular Biology, Inc.

---

Technology

The Paragon Algorithm, a Next Generation Search Engine That Uses Sequence Temperature Values and Feature Probabilities to Identify Peptides from Tandem Mass Spectra^*,S

Ignat V. Shilov, Sean L. Seymour^,, Alpesh A. Patel, Alex Loboda, Wilfred H. Tang, Sean P. Keating^¶, Christie L. Hunter, Lydia M. Nuwaysir and Daniel A. Schaeffer

From Applied Biosystems/MDS Sciex, Foster City, California 94404

The Paragon^TM Algorithm, a novel database search engine for the identification of peptides from tandem mass spectrometry data, is presented. Sequence Temperature Values are computed using a sequence tag algorithm, allowing the degree of implication by an MS/MS spectrum of each region of a database to be determined on a continuum. Counter to conventional approaches, features such as modifications, substitutions, and cleavage events are modeled with probabilities rather than by discrete user-controlled settings to consider or not consider a feature. The use of feature probabilities in conjunction with Sequence Temperature Values allows for a very large increase in the effective search space with only a very small increase in the actual number of hypotheses that must be scored. The algorithm has a new kind of user interface that removes the user expertise requirement, presenting control settings in the language of the laboratory that are translated to optimal algorithmic settings. To validate this new algorithm, a comparison with Mascot is presented for a series of analogous searches to explore the relative impact of increasing search space probed with Mascot by relaxing the tryptic digestion conformance requirements from trypsin to semitrypsin to no enzyme and with the Paragon Algorithm using its Rapid mode and Thorough mode with and without tryptic specificity. Although they performed similarly for small search space, dramatic differences were observed in large search space. With the Paragon Algorithm, hundreds of biological and artifact modifications, all possible substitutions, and all levels of conformance to the expected digestion pattern can be searched in a single search step, yet the typical cost in search time is only 2–5 times that of conventional small search space. Despite this large increase in effective search space, there is no drastic loss of discrimination that typically accompanies the exploration of large search space.

CiteULike    Complore    Connotea    Del.icio.us    Digg    Reddit    Technorati    What's this?

This article has been cited by other articles:

				N. Ozlu, F. Monigatti, B. Y. Renard, C. M. Field, H. Steen, T. J. Mitchison, and J. J. Steen Binding Partner Switching on Microtubules and Aurora-B in the Mitosis to Cytokinesis Transition Mol. Cell. Proteomics, February 1, 2010; 9(2): 336 - 350. [Abstract] [Full Text] [PDF]

				M. J. Saller, F. Fusetti, and A. J. M. Driessen Bacillus subtilis SpoIIIJ and YqjG Function in Membrane Protein Biogenesis J. Bacteriol., November 1, 2009; 191(21): 6749 - 6757. [Abstract] [Full Text] [PDF]

				M. S. Riedl, P. D. Braun, K. F. Kitto, S. A. Roiko, L. B. Anderson, C. N. Honda, C. A. Fairbanks, and L. Vulchanova Proteomic Analysis Uncovers Novel Actions of the Neurosecretory Protein VGF in Nociceptive Processing J. Neurosci., October 21, 2009; 29(42): 13377 - 13388. [Abstract] [Full Text] [PDF]

				L. Reyes, S. Alvarez, A. Allam, M. Reinhard, and M. B. Brown Complicated Urinary Tract Infection Is Associated with Uroepithelial Expression of Proinflammatory Protein S100A8 Infect. Immun., October 1, 2009; 77(10): 4265 - 4274. [Abstract] [Full Text] [PDF]

				D. Kobayashi, J. Kumagai, T. Morikawa, M. Wilson-Morifuji, A. Wilson, A. Irie, and N. Araki An Integrated Approach of Differential Mass Spectrometry and Gene Ontology Analysis Identified Novel Proteins Regulating Neuronal Differentiation and Survival Mol. Cell. Proteomics, October 1, 2009; 8(10): 2350 - 2367. [Abstract] [Full Text] [PDF]

				J. D. McCully, M. K. Bhasin, C. Daly, M. C. Guerrero, S. Dillon, T. A. Liberman, D. B. Cowan, J. D. Mably, F. X. McGowan, and S. Levitsky Transcriptomic and proteomic analysis of global ischemia and cardioprotection in the rabbit heart Physiol Genomics, July 9, 2009; 38(2): 125 - 137. [Abstract] [Full Text] [PDF]

				Y. Liu, B. K. Law, and H. Luesch Apratoxin A Reversibly Inhibits the Secretory Pathway by Preventing Cotranslational Translocation Mol. Pharmacol., July 1, 2009; 76(1): 91 - 104. [Abstract] [Full Text] [PDF]

				S. Kim, N. Bandeira, and P. A. Pevzner Spectral Profiles, a Novel Representation of Tandem Mass Spectra and Their Applications for de Novo Peptide Sequencing and Identification Mol. Cell. Proteomics, June 1, 2009; 8(6): 1391 - 1400. [Abstract] [Full Text] [PDF]

				X. Ge, H. H. Loh, and P.-Y. Law {micro}-Opioid Receptor Cell Surface Expression Is Regulated by Its Direct Interaction with Ribophorin I Mol. Pharmacol., June 1, 2009; 75(6): 1307 - 1316. [Abstract] [Full Text] [PDF]

				M. Zhu, S. Dai, S. McClung, X. Yan, and S. Chen Functional Differentiation of Brassica napus Guard Cells and Mesophyll Cells Revealed by Comparative Proteomics Mol. Cell. Proteomics, April 1, 2009; 8(4): 752 - 766. [Abstract] [Full Text] [PDF]

				H. Roelofsen, M. Dijkstra, D. Weening, M. P. de Vries, A. Hoek, and R. J. Vonk Comparison of Isotope-labeled Amino Acid Incorporation Rates (CILAIR) Provides a Quantitative Method to Study Tissue Secretomes Mol. Cell. Proteomics, February 1, 2009; 8(2): 316 - 324. [Abstract] [Full Text] [PDF]

				S. Kim, N. Gupta, N. Bandeira, and P. A. Pevzner Spectral Dictionaries: Integrating de novo Peptide Sequencing with Database Search of Tandem Mass Spectra Mol. Cell. Proteomics, January 1, 2009; 8(1): 53 - 69. [Abstract] [Full Text] [PDF]

				Z. Zhao, W. Zhang, B. A. Stanley, and S. M. Assmann Functional Proteomics of Arabidopsis thaliana Guard Cells Uncovers New Stomatal Signaling Pathways PLANT CELL, December 1, 2008; 20(12): 3210 - 3226. [Abstract] [Full Text] [PDF]

				H. Lu, Y. Yang, E. M. Allister, N. Wijesekara, and M. B. Wheeler The Identification of Potential Factors Associated with the Development of Type 2 Diabetes: A Quantitative Proteomics Approach Mol. Cell. Proteomics, August 1, 2008; 7(8): 1434 - 1451. [Abstract] [Full Text] [PDF]

				R. Ralhan, L. V. DeSouza, A. Matta, S. Chandra Tripathi, S. Ghanny, S. Datta Gupta, S. Bahadur, and K. W. M. Siu Discovery and Verification of Head-and-neck Cancer Biomarkers by Differential Protein Expression Analysis Using iTRAQ Labeling, Multidimensional Liquid Chromatography, and Tandem Mass Spectrometry Mol. Cell. Proteomics, June 1, 2008; 7(6): 1162 - 1173. [Abstract] [Full Text] [PDF]

				A. Pierce, R. D. Unwin, C. A. Evans, S. Griffiths, L. Carney, L. Zhang, E. Jaworska, C.-F. Lee, D. Blinco, M. J. Okoniewski, et al. Eight-channel iTRAQ Enables Comparison of the Activity of Six Leukemogenic Tyrosine Kinases Mol. Cell. Proteomics, May 1, 2008; 7(5): 853 - 863. [Abstract] [Full Text] [PDF]

				C. L. Organ, M. H. Schweitzer, W. Zheng, L. M. Freimark, L. C. Cantley, and J. M. Asara Molecular Phylogenetics of Mastodon and Tyrannosaurus rex Science, April 25, 2008; 320(5875): 499 - 499. [Abstract] [Full Text] [PDF]

				A. K. Yocum, T. E. Gratsch, N. Leff, J. R. Strahler, C. L. Hunter, A. K. Walker, G. Michailidis, G. S. Omenn, K. S. O'Shea, and P. C. Andrews Coupled Global and Targeted Proteomics of Human Embryonic Stem Cells during Induced Differentiation Mol. Cell. Proteomics, April 1, 2008; 7(4): 750 - 767. [Abstract] [Full Text] [PDF]

				J. Noirel, S. Y. Ow, G. Sanguinetti, A. Jaramillo, and P. C. Wright Automated extraction of meaningful pathways from quantitative proteomics data Briefings in Functional Genomics, March 7, 2008; (2008) eln011v1. [Abstract] [Full Text] [PDF]

				F. Kassie, L. B. Anderson, L. Higgins, Y. Pan, I. Matise, M. Negia, P. Upadhyaya, M. Wang, and S. S. Hecht Chemopreventive agents modulate the protein expression profile of 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone plus benzo[a]pyrene-induced lung tumors in A/J mice Carcinogenesis, March 1, 2008; 29(3): 610 - 619. [Abstract] [Full Text] [PDF]