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The Encyclopedia of Proteome Dynamics: a big data ecosystem for (prote)omics

Driven by improvements in speed and resolution of mass spectrometers (MS), the field of proteomics, which involves the large-scale detection and analysis of proteins in cells, tissues and organisms, continues to expand in scale and complexity. There is a resulting growth in datasets of both raw MS f...

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Detalles Bibliográficos
Autores principales: Brenes, Alejandro, Afzal, Vackar, Kent, Robert, Lamond, Angus I
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5753345/
https://www.ncbi.nlm.nih.gov/pubmed/28981707
http://dx.doi.org/10.1093/nar/gkx807
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author Brenes, Alejandro
Afzal, Vackar
Kent, Robert
Lamond, Angus I
author_facet Brenes, Alejandro
Afzal, Vackar
Kent, Robert
Lamond, Angus I
author_sort Brenes, Alejandro
collection PubMed
description Driven by improvements in speed and resolution of mass spectrometers (MS), the field of proteomics, which involves the large-scale detection and analysis of proteins in cells, tissues and organisms, continues to expand in scale and complexity. There is a resulting growth in datasets of both raw MS files and processed peptide and protein identifications. MS-based proteomics technology is also used increasingly to measure additional protein properties affecting cellular function and disease mechanisms, including post-translational modifications, protein–protein interactions, subcellular and tissue distributions. Consequently, biologists and clinicians need innovative tools to conveniently analyse, visualize and explore such large, complex proteomics data and to integrate it with genomics and other related large-scale datasets. We have created the Encyclopedia of Proteome Dynamics (EPD) to meet this need (https://peptracker.com/epd/). The EPD combines a polyglot persistent database and web-application that provides open access to integrated proteomics data for >30 000 proteins from published studies on human cells and model organisms. It is designed to provide a user-friendly interface, featuring graphical navigation with interactive visualizations that facilitate powerful data exploration in an intuitive manner. The EPD offers a flexible and scalable ecosystem to integrate proteomics data with genomics information, RNA expression and other related, large-scale datasets.
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spelling pubmed-57533452018-01-05 The Encyclopedia of Proteome Dynamics: a big data ecosystem for (prote)omics Brenes, Alejandro Afzal, Vackar Kent, Robert Lamond, Angus I Nucleic Acids Res Database Issue Driven by improvements in speed and resolution of mass spectrometers (MS), the field of proteomics, which involves the large-scale detection and analysis of proteins in cells, tissues and organisms, continues to expand in scale and complexity. There is a resulting growth in datasets of both raw MS files and processed peptide and protein identifications. MS-based proteomics technology is also used increasingly to measure additional protein properties affecting cellular function and disease mechanisms, including post-translational modifications, protein–protein interactions, subcellular and tissue distributions. Consequently, biologists and clinicians need innovative tools to conveniently analyse, visualize and explore such large, complex proteomics data and to integrate it with genomics and other related large-scale datasets. We have created the Encyclopedia of Proteome Dynamics (EPD) to meet this need (https://peptracker.com/epd/). The EPD combines a polyglot persistent database and web-application that provides open access to integrated proteomics data for >30 000 proteins from published studies on human cells and model organisms. It is designed to provide a user-friendly interface, featuring graphical navigation with interactive visualizations that facilitate powerful data exploration in an intuitive manner. The EPD offers a flexible and scalable ecosystem to integrate proteomics data with genomics information, RNA expression and other related, large-scale datasets. Oxford University Press 2018-01-04 2017-09-07 /pmc/articles/PMC5753345/ /pubmed/28981707 http://dx.doi.org/10.1093/nar/gkx807 Text en © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Database Issue
Brenes, Alejandro
Afzal, Vackar
Kent, Robert
Lamond, Angus I
The Encyclopedia of Proteome Dynamics: a big data ecosystem for (prote)omics
title The Encyclopedia of Proteome Dynamics: a big data ecosystem for (prote)omics
title_full The Encyclopedia of Proteome Dynamics: a big data ecosystem for (prote)omics
title_fullStr The Encyclopedia of Proteome Dynamics: a big data ecosystem for (prote)omics
title_full_unstemmed The Encyclopedia of Proteome Dynamics: a big data ecosystem for (prote)omics
title_short The Encyclopedia of Proteome Dynamics: a big data ecosystem for (prote)omics
title_sort encyclopedia of proteome dynamics: a big data ecosystem for (prote)omics
topic Database Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5753345/
https://www.ncbi.nlm.nih.gov/pubmed/28981707
http://dx.doi.org/10.1093/nar/gkx807
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