Literature DB >> 18451766

PeptideAtlas: a resource for target selection for emerging targeted proteomics workflows.

Eric W Deutsch1, Henry Lam, Ruedi Aebersold.   

Abstract

A crucial part of a successful systems biology experiment is an assay that provides reliable, quantitative measurements for each of the components in the system being studied. For proteomics to be a key part of such studies, it must deliver accurate quantification of all the components in the system for each tested perturbation without any gaps in the data. This will require a new approach to proteomics that is based on emerging targeted quantitative mass spectrometry techniques. The PeptideAtlas Project comprises a growing, publicly accessible database of peptides identified in many tandem mass spectrometry proteomics studies and software tools that allow the building of PeptideAtlas, as well as its use by the research community. Here, we describe the PeptideAtlas Project, its contents and components, and show how together they provide a unique platform to select and validate mass spectrometry targets, thereby allowing the next revolution in proteomics.

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Year:  2008        PMID: 18451766      PMCID: PMC2373374          DOI: 10.1038/embor.2008.56

Source DB:  PubMed          Journal:  EMBO Rep        ISSN: 1469-221X            Impact factor:   8.807


  26 in total

1.  Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search.

Authors:  Andrew Keller; Alexey I Nesvizhskii; Eugene Kolker; Ruedi Aebersold
Journal:  Anal Chem       Date:  2002-10-15       Impact factor: 6.986

2.  The need for a public proteomics repository.

Authors:  John T Prince; Mark W Carlson; Rong Wang; Peng Lu; Edward M Marcotte
Journal:  Nat Biotechnol       Date:  2004-04       Impact factor: 54.908

3.  TANDEM: matching proteins with tandem mass spectra.

Authors:  Robertson Craig; Ronald C Beavis
Journal:  Bioinformatics       Date:  2004-02-19       Impact factor: 6.937

4.  Open source system for analyzing, validating, and storing protein identification data.

Authors:  Robertson Craig; John P Cortens; Ronald C Beavis
Journal:  J Proteome Res       Date:  2004 Nov-Dec       Impact factor: 4.466

5.  Computational prediction of proteotypic peptides for quantitative proteomics.

Authors:  Parag Mallick; Markus Schirle; Sharon S Chen; Mark R Flory; Hookeun Lee; Daniel Martin; Jeffrey Ranish; Brian Raught; Robert Schmitt; Thilo Werner; Bernhard Kuster; Ruedi Aebersold
Journal:  Nat Biotechnol       Date:  2006-12-31       Impact factor: 54.908

6.  Development and validation of a spectral library searching method for peptide identification from MS/MS.

Authors:  Henry Lam; Eric W Deutsch; James S Eddes; Jimmy K Eng; Nichole King; Stephen E Stein; Ruedi Aebersold
Journal:  Proteomics       Date:  2007-03       Impact factor: 3.984

7.  High sensitivity detection of plasma proteins by multiple reaction monitoring of N-glycosites.

Authors:  Jianru Stahl-Zeng; Vinzenz Lange; Reto Ossola; Katrin Eckhardt; Wilhelm Krek; Ruedi Aebersold; Bruno Domon
Journal:  Mol Cell Proteomics       Date:  2007-07-20       Impact factor: 5.911

8.  SBEAMS-Microarray: database software supporting genomic expression analyses for systems biology.

Authors:  Bruz Marzolf; Eric W Deutsch; Patrick Moss; David Campbell; Michael H Johnson; Timothy Galitski
Journal:  BMC Bioinformatics       Date:  2006-06-06       Impact factor: 3.169

9.  Integration with the human genome of peptide sequences obtained by high-throughput mass spectrometry.

Authors:  Frank Desiere; Eric W Deutsch; Alexey I Nesvizhskii; Parag Mallick; Nichole L King; Jimmy K Eng; Alan Aderem; Rose Boyle; Erich Brunner; Samuel Donohoe; Nelson Fausto; Ernst Hafen; Lee Hood; Michael G Katze; Kathleen A Kennedy; Floyd Kregenow; Hookeun Lee; Biaoyang Lin; Dan Martin; Jeffrey A Ranish; David J Rawlings; Lawrence E Samelson; Yuzuru Shiio; Julian D Watts; Bernd Wollscheid; Michael E Wright; Wei Yan; Lihong Yang; Eugene C Yi; Hui Zhang; Ruedi Aebersold
Journal:  Genome Biol       Date:  2004-12-10       Impact factor: 13.583

10.  Ensembl 2007.

Authors:  T J P Hubbard; B L Aken; K Beal; B Ballester; M Caccamo; Y Chen; L Clarke; G Coates; F Cunningham; T Cutts; T Down; S C Dyer; S Fitzgerald; J Fernandez-Banet; S Graf; S Haider; M Hammond; J Herrero; R Holland; K Howe; K Howe; N Johnson; A Kahari; D Keefe; F Kokocinski; E Kulesha; D Lawson; I Longden; C Melsopp; K Megy; P Meidl; B Ouverdin; A Parker; A Prlic; S Rice; D Rios; M Schuster; I Sealy; J Severin; G Slater; D Smedley; G Spudich; S Trevanion; A Vilella; J Vogel; S White; M Wood; T Cox; V Curwen; R Durbin; X M Fernandez-Suarez; P Flicek; A Kasprzyk; G Proctor; S Searle; J Smith; A Ureta-Vidal; E Birney
Journal:  Nucleic Acids Res       Date:  2006-12-05       Impact factor: 16.971

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  207 in total

1.  Verification of male infertility biomarkers in seminal plasma by multiplex selected reaction monitoring assay.

Authors:  Andrei P Drabovich; Keith Jarvi; Eleftherios P Diamandis
Journal:  Mol Cell Proteomics       Date:  2011-09-20       Impact factor: 5.911

2.  Recommendations for mass spectrometry data quality metrics for open access data (corollary to the Amsterdam Principles).

Authors:  Christopher R Kinsinger; James Apffel; Mark Baker; Xiaopeng Bian; Christoph H Borchers; Ralph Bradshaw; Mi-Youn Brusniak; Daniel W Chan; Eric W Deutsch; Bruno Domon; Jeff Gorman; Rudolf Grimm; William Hancock; Henning Hermjakob; David Horn; Christie Hunter; Patrik Kolar; Hans-Joachim Kraus; Hanno Langen; Rune Linding; Robert L Moritz; Gilbert S Omenn; Ron Orlando; Akhilesh Pandey; Peipei Ping; Amir Rahbar; Robert Rivers; Sean L Seymour; Richard J Simpson; Douglas Slotta; Richard D Smith; Stephen E Stein; David L Tabb; Danilo Tagle; John R Yates; Henry Rodriguez
Journal:  Mol Cell Proteomics       Date:  2011-11-03       Impact factor: 5.911

3.  Functional proteomics establishes the interaction of SIRT7 with chromatin remodeling complexes and expands its role in regulation of RNA polymerase I transcription.

Authors:  Yuan-Chin Tsai; Todd M Greco; Apaporn Boonmee; Yana Miteva; Ileana M Cristea
Journal:  Mol Cell Proteomics       Date:  2011-12-05       Impact factor: 5.911

4.  Combining ultracentrifugation and peptide termini group-specific immunoprecipitation for multiplex plasma protein analysis.

Authors:  Sonja Volk; Thomas D Schreiber; David Eisen; Calvin Wiese; Hannes Planatscher; Christopher J Pynn; Dieter Stoll; Markus F Templin; Thomas O Joos; Oliver Pötz
Journal:  Mol Cell Proteomics       Date:  2012-04-23       Impact factor: 5.911

5.  A computational tool to detect and avoid redundancy in selected reaction monitoring.

Authors:  Hannes Röst; Lars Malmström; Ruedi Aebersold
Journal:  Mol Cell Proteomics       Date:  2012-04-24       Impact factor: 5.911

6.  mz5: space- and time-efficient storage of mass spectrometry data sets.

Authors:  Mathias Wilhelm; Marc Kirchner; Judith A J Steen; Hanno Steen
Journal:  Mol Cell Proteomics       Date:  2011-09-29       Impact factor: 5.911

Review 7.  Selected reaction monitoring-based proteomics: workflows, potential, pitfalls and future directions.

Authors:  Paola Picotti; Ruedi Aebersold
Journal:  Nat Methods       Date:  2012-05-30       Impact factor: 28.547

8.  Accounting for population variation in targeted proteomics.

Authors:  Grant M Fujimoto; Matthew E Monroe; Larissa Rodriguez; Chaochao Wu; Brendan MacLean; Richard D Smith; Michael J MacCoss; Samuel H Payne
Journal:  J Proteome Res       Date:  2013-12-16       Impact factor: 4.466

Review 9.  Integrating omics technologies to study pulmonary physiology and pathology at the systems level.

Authors:  Ravi Ramesh Pathak; Vrushank Davé
Journal:  Cell Physiol Biochem       Date:  2014-04-28

10.  The Equine PeptideAtlas: a resource for developing proteomics-based veterinary research.

Authors:  Louise Bundgaard; Stine Jacobsen; Mette A Sørensen; Zhi Sun; Eric W Deutsch; Robert L Moritz; Emøke Bendixen
Journal:  Proteomics       Date:  2014-02-16       Impact factor: 3.984

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