The need for a public proteomics repository

Prince, John T.; Carlson, Mark W.; Wang, Rong; Lu, Ping; Marcotte, Edward M.

doi:10.1038/nbt0404-471

Cited by 151 publications

(98 citation statements)

References 25 publications

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“…A library of "consensus spectra" derived from the CID of 34 426 peptide ions was created from 43 LC-MS/MS datasets of tryptic digests of baker's yeast (S. cerevisiae), taken mostly from public data repositories [23][24][25][26][27], and released as part of the freely available NIST Library of Peptide Ion Fragmentation Spectra (The NIST Library of Peptide Ion Fragmentation Spectra, June 2006 Version. Available for download at http://www.peptideatlas/ org/SpectralLibraryDownload.php.…”

Section: Creation Of Consensus Spectral Librariesmentioning

confidence: 99%

“…With the explosion of proteomics data in recent years, the time is ripe to revisit the idea, with some preliminary demonstration of success being reported in two recent publications [21,22]. The availability of online data repositories developed in recent years [23][24][25][26][27], as well as emerging unified standards for representing shotgun proteomics data, such as mzXML [28] and mzData (http://psi dev.sourceforge.net/ms/#mzdata), have made it possible to collect and catalog an adequate set of peptide CID spectra to create a high-quality spectral library. For the spectral library to be comprehensive (containing sufficient entries to cover a high proportion of the observed proteome) and accurate (containing high-quality and truly characteristic MS/MS spectra that can be confidently mapped to peptides), it is important to gather raw MS/MS spectra from a wide variety of sources, to identify them as accurately as possible, to filter out the inevitable false positives, and to process the spectra to reduce noise and other experimental artifacts.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2007

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A notable inefficiency of shotgun proteomics experiments is the repeated rediscovery of the same identifiable peptides by sequence database searching methods, which often are time-consuming and error-prone. A more precise and efficient method, in which previously observed and identified peptide MS/MS spectra are catalogued and condensed into searchable spectral libraries to allow new identifications by spectral matching, is seen as a promising alternative. To that end, an open-source, functionally complete, high-throughput and readily extensible MS/MS spectral searching tool, SpectraST, was developed. A high-quality spectral library was constructed by combining the high-confidence identifications of millions of spectra taken from various data repositories and searched using four sequence search engines. The resulting library consists of over 30 000 spectra for Saccharomyces cerevisiae. Using this library, SpectraST vastly outperforms the sequence search engine SEQUEST in terms of speed and the ability to discriminate good and bad hits. A unique advantage of SpectraST is its full integration into the popular Trans Proteomic Pipeline suite of software, which facilitates user adoption and provides important functionalities such as peptide and protein probability assignment, quantification, and data visualization. This method of spectral library searching is especially suited for targeted proteomics applications, offering superior performance to traditional sequence searching.

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Section: Creation Of Consensus Spectral Librariesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

et al. 2007

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“…utexas.edu/OPD by E. M. Marcotte's laboratory at the University of Texas, also see reference [6]. The raw data file is found under the Miscellaneous section, acc#: opd00099_PROTS, 6prot_75pmol_each.…”

Section: Methodsmentioning

confidence: 99%

Generation of asparagine-linked glycan structure databases and their use

Gao¹

2009

J. Am. Soc. Mass Spectrom.

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Asparagine linked glycans (N-glycans) are important in biological processes. Yet, their structural complexity and lack of databases hinder progress in glycomics and glycobiology. We present a way for in silico generation of very large N-glycan structure databases and their use in high throughput composition and primary structure determination of N-glycans attached to peptides, based on CID (collision induced dissociation) MS/MS (tandem mass spectrometric data).

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“…Since this relative inaccessibility of proteomics data presents a considerable stumbling block on the way to making all these identifications really count for life sciences, the construction of a centralized, freely accessible repository for proteomics data is one of the primary requirements in proteomics today [5,6]. In a single sentence: publicly available data needs to become publicly accessible data.…”

Section: Introductionmentioning

confidence: 99%

PRIDE: The proteomics identifications database

et al. 2005

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The advent of high-throughput proteomics has enabled the identification of ever increasing numbers of proteins. Correspondingly, the number of publications centered on these protein identifications has increased dramatically. With the first results of the HUPO Plasma Proteome Project being analyzed and many other large-scale proteomics projects about to disseminate their data, this trend is not likely to flatten out any time soon. However, the publication mechanism of these identified proteins has lagged behind in technical terms. Often very long lists of identifications are either published directly with the article, resulting in both a voluminous and rather tedious read, or are included on the publisher's website as supplementary information. In either case, these lists are typically only provided as portable document format documents with a custom-made layout, making it practically impossible for computer programs to interpret them, let alone efficiently query them. Here we propose the proteomics identifications (PRIDE) database (http://www.ebi.ac.uk/pride) as a means to finally turn publicly available data into publicly accessible data. PRIDE offers a web-based query interface, a user-friendly data upload facility, and a documented application programming interface for direct computational access. The complete PRIDE database, source code, data, and support tools are freely available for web access or download and local installation.

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The need for a public proteomics repository

Cited by 151 publications

References 25 publications

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

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

Generation of asparagine-linked glycan structure databases and their use

PRIDE: The proteomics identifications database

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