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ProteomicsDB

ProteomicsDB (https://www.ProteomicsDB.org) is a protein-centric in-memory database for the exploration of large collections of quantitative mass spectrometry-based proteomics data. ProteomicsDB was first released in 2014 to enable the interactive exploration of the first draft of the human proteome...

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Autores principales: Schmidt, Tobias, Samaras, Patroklos, Frejno, Martin, Gessulat, Siegfried, Barnert, Maximilian, Kienegger, Harald, Krcmar, Helmut, Schlegl, Judith, Ehrlich, Hans-Christian, Aiche, Stephan, Kuster, Bernhard, Wilhelm, Mathias
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5753189/
https://www.ncbi.nlm.nih.gov/pubmed/29106664
http://dx.doi.org/10.1093/nar/gkx1029
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author Schmidt, Tobias
Samaras, Patroklos
Frejno, Martin
Gessulat, Siegfried
Barnert, Maximilian
Kienegger, Harald
Krcmar, Helmut
Schlegl, Judith
Ehrlich, Hans-Christian
Aiche, Stephan
Kuster, Bernhard
Wilhelm, Mathias
author_facet Schmidt, Tobias
Samaras, Patroklos
Frejno, Martin
Gessulat, Siegfried
Barnert, Maximilian
Kienegger, Harald
Krcmar, Helmut
Schlegl, Judith
Ehrlich, Hans-Christian
Aiche, Stephan
Kuster, Bernhard
Wilhelm, Mathias
author_sort Schmidt, Tobias
collection PubMed
description ProteomicsDB (https://www.ProteomicsDB.org) is a protein-centric in-memory database for the exploration of large collections of quantitative mass spectrometry-based proteomics data. ProteomicsDB was first released in 2014 to enable the interactive exploration of the first draft of the human proteome. To date, it contains quantitative data from 78 projects totalling over 19k LC–MS/MS experiments. A standardized analysis pipeline enables comparisons between multiple datasets to facilitate the exploration of protein expression across hundreds of tissues, body fluids and cell lines. We recently extended the data model to enable the storage and integrated visualization of other quantitative omics data. This includes transcriptomics data from e.g. NCBI GEO, protein–protein interaction information from STRING, functional annotations from KEGG, drug-sensitivity/selectivity data from several public sources and reference mass spectra from the ProteomeTools project. The extended functionality transforms ProteomicsDB into a multi-purpose resource connecting quantification and meta-data for each protein. The rich user interface helps researchers to navigate all data sources in either a protein-centric or multi-protein-centric manner. Several options are available to download data manually, while our application programming interface enables accessing quantitative data systematically.
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spelling pubmed-57531892018-01-05 ProteomicsDB Schmidt, Tobias Samaras, Patroklos Frejno, Martin Gessulat, Siegfried Barnert, Maximilian Kienegger, Harald Krcmar, Helmut Schlegl, Judith Ehrlich, Hans-Christian Aiche, Stephan Kuster, Bernhard Wilhelm, Mathias Nucleic Acids Res Database Issue ProteomicsDB (https://www.ProteomicsDB.org) is a protein-centric in-memory database for the exploration of large collections of quantitative mass spectrometry-based proteomics data. ProteomicsDB was first released in 2014 to enable the interactive exploration of the first draft of the human proteome. To date, it contains quantitative data from 78 projects totalling over 19k LC–MS/MS experiments. A standardized analysis pipeline enables comparisons between multiple datasets to facilitate the exploration of protein expression across hundreds of tissues, body fluids and cell lines. We recently extended the data model to enable the storage and integrated visualization of other quantitative omics data. This includes transcriptomics data from e.g. NCBI GEO, protein–protein interaction information from STRING, functional annotations from KEGG, drug-sensitivity/selectivity data from several public sources and reference mass spectra from the ProteomeTools project. The extended functionality transforms ProteomicsDB into a multi-purpose resource connecting quantification and meta-data for each protein. The rich user interface helps researchers to navigate all data sources in either a protein-centric or multi-protein-centric manner. Several options are available to download data manually, while our application programming interface enables accessing quantitative data systematically. Oxford University Press 2018-01-04 2017-11-02 /pmc/articles/PMC5753189/ /pubmed/29106664 http://dx.doi.org/10.1093/nar/gkx1029 Text en © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Database Issue
Schmidt, Tobias
Samaras, Patroklos
Frejno, Martin
Gessulat, Siegfried
Barnert, Maximilian
Kienegger, Harald
Krcmar, Helmut
Schlegl, Judith
Ehrlich, Hans-Christian
Aiche, Stephan
Kuster, Bernhard
Wilhelm, Mathias
ProteomicsDB
title ProteomicsDB
title_full ProteomicsDB
title_fullStr ProteomicsDB
title_full_unstemmed ProteomicsDB
title_short ProteomicsDB
title_sort proteomicsdb
topic Database Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5753189/
https://www.ncbi.nlm.nih.gov/pubmed/29106664
http://dx.doi.org/10.1093/nar/gkx1029
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