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Literature DB >> 23361086

PRIDE Cluster: building a consensus of proteomics data.

Johannes Griss, Joseph M Foster, Henning Hermjakob, Juan Antonio Vizcaíno.

Abstract

Mesh：

Year: 2013 PMID： 23361086 PMCID： PMC3667236 DOI： 10.1038/nmeth.2343

Source DB: PubMed Journal: Nat Methods ISSN： 1548-7091 Impact factor: 28.547

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5 in total

1. Target-decoy approach and false discovery rate: when things may go wrong.

Authors: Nitin Gupta; Nuno Bandeira; Uri Keich; Pavel A Pevzner
Journal: J Am Soc Mass Spectrom Date: 2011-05-05 Impact factor: 3.109

2. Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry.

Authors: Joshua E Elias; Steven P Gygi
Journal: Nat Methods Date: 2007-03 Impact factor: 28.547

3. PRIDE: quality control in a proteomics data repository.

Authors: Attila Csordas; David Ovelleiro; Rui Wang; Joseph M Foster; Daniel Ríos; Juan Antonio Vizcaíno; Henning Hermjakob
Journal: Database (Oxford) Date: 2012-03-20 Impact factor: 3.451

4. Spectral archives: extending spectral libraries to analyze both identified and unidentified spectra.

Authors: Ari M Frank; Matthew E Monroe; Anuj R Shah; Jeremy J Carver; Nuno Bandeira; Ronald J Moore; Gordon A Anderson; Richard D Smith; Pavel A Pevzner
Journal: Nat Methods Date: 2011-05-15 Impact factor: 28.547

5. The Proteomics Identifications database: 2010 update.

Authors: Juan Antonio Vizcaíno; Richard Côté; Florian Reisinger; Harald Barsnes; Joseph M Foster; Jonathan Rameseder; Henning Hermjakob; Lennart Martens
Journal: Nucleic Acids Res Date: 2009-11-11 Impact factor: 16.971

5 in total

26 in total

1. Proteomics INTegrator (PINT): An Online Tool To Store, Query, and Visualize Large Proteomics Experiment Results.

Authors: Salvador Martínez-Bartolomé; Tom Casimir Bamberger; Mathieu Lavallée-Adam; Daniel B McClatchy; John R Yates
Journal: J Proteome Res Date: 2019-07-01 Impact factor: 4.466

2. A Meta-proteogenomic Approach to Peptide Identification Incorporating Assembly Uncertainty and Genomic Variation.

Authors: Sujun Li; Haixu Tang; Yuzhen Ye
Journal: Mol Cell Proteomics Date: 2019-05-29 Impact factor: 5.911

Review 3. Trans-Proteomic Pipeline, a standardized data processing pipeline for large-scale reproducible proteomics informatics.

Authors: Eric W Deutsch; Luis Mendoza; David Shteynberg; Joseph Slagel; Zhi Sun; Robert L Moritz
Journal: Proteomics Clin Appl Date: 2015-04-02 Impact factor: 3.494

4. The Human Immunopeptidome Project: A Roadmap to Predict and Treat Immune Diseases.

Authors: Juan Antonio Vizcaíno; Peter Kubiniok; Kevin A Kovalchik; Qing Ma; Jérôme D Duquette; Ian Mongrain; Eric W Deutsch; Bjoern Peters; Alessandro Sette; Isabelle Sirois; Etienne Caron
Journal: Mol Cell Proteomics Date: 2019-11-19 Impact factor: 5.911

5. CHICKN: extraction of peptide chromatographic elution profiles from large scale mass spectrometry data by means of Wasserstein compressive hierarchical cluster analysis.

Authors: Olga Permiakova; Romain Guibert; Alexandra Kraut; Thomas Fortin; Anne-Marie Hesse; Thomas Burger
Journal: BMC Bioinformatics Date: 2021-02-12 Impact factor: 3.169

PRIDE Cluster: building a consensus of proteomics data.

1. Target-decoy approach and false discovery rate: when things may go wrong.

2. Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry.

3. PRIDE: quality control in a proteomics data repository.

4. Spectral archives: extending spectral libraries to analyze both identified and unidentified spectra.

5. The Proteomics Identifications database: 2010 update.

1. Proteomics INTegrator (PINT): An Online Tool To Store, Query, and Visualize Large Proteomics Experiment Results.

2. A Meta-proteogenomic Approach to Peptide Identification Incorporating Assembly Uncertainty and Genomic Variation.

Review 3. Trans-Proteomic Pipeline, a standardized data processing pipeline for large-scale reproducible proteomics informatics.

4. The Human Immunopeptidome Project: A Roadmap to Predict and Treat Immune Diseases.

5. CHICKN: extraction of peptide chromatographic elution profiles from large scale mass spectrometry data by means of Wasserstein compressive hierarchical cluster analysis.

6. A learned embedding for efficient joint analysis of millions of mass spectra.

7. Greazy: Open-Source Software for Automated Phospholipid Tandem Mass Spectrometry Identification.

8. Fast Open Modification Spectral Library Searching through Approximate Nearest Neighbor Indexing.

9. Integration of Proteomics and Other Omics Data.

10. Large-scale tandem mass spectrum clustering using fast nearest neighbor searching.