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A Golden Age for Working with Public Proteomics Data
Data sharing in mass spectrometry (MS)-based proteomics is becoming a common scientific practice, as is now common in the case of other, more mature ‘omics’ disciplines like genomics and transcriptomics. We want to highlight that this situation, unprecedented in the field, opens a plethora of opport...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Trends Journals
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5414595/ https://www.ncbi.nlm.nih.gov/pubmed/28118949 http://dx.doi.org/10.1016/j.tibs.2017.01.001 |
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author | Martens, Lennart Vizcaíno, Juan Antonio |
author_facet | Martens, Lennart Vizcaíno, Juan Antonio |
author_sort | Martens, Lennart |
collection | PubMed |
description | Data sharing in mass spectrometry (MS)-based proteomics is becoming a common scientific practice, as is now common in the case of other, more mature ‘omics’ disciplines like genomics and transcriptomics. We want to highlight that this situation, unprecedented in the field, opens a plethora of opportunities for data scientists. First, we explain in some detail some of the work already achieved, such as systematic reanalysis efforts. We also explain existing applications of public proteomics data, such as proteogenomics and the creation of spectral libraries and spectral archives. Finally, we discuss the main existing challenges and mention the first attempts to combine public proteomics data with other types of omics data sets. |
format | Online Article Text |
id | pubmed-5414595 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Elsevier Trends Journals |
record_format | MEDLINE/PubMed |
spelling | pubmed-54145952017-05-10 A Golden Age for Working with Public Proteomics Data Martens, Lennart Vizcaíno, Juan Antonio Trends Biochem Sci Opinion Data sharing in mass spectrometry (MS)-based proteomics is becoming a common scientific practice, as is now common in the case of other, more mature ‘omics’ disciplines like genomics and transcriptomics. We want to highlight that this situation, unprecedented in the field, opens a plethora of opportunities for data scientists. First, we explain in some detail some of the work already achieved, such as systematic reanalysis efforts. We also explain existing applications of public proteomics data, such as proteogenomics and the creation of spectral libraries and spectral archives. Finally, we discuss the main existing challenges and mention the first attempts to combine public proteomics data with other types of omics data sets. Elsevier Trends Journals 2017-05 /pmc/articles/PMC5414595/ /pubmed/28118949 http://dx.doi.org/10.1016/j.tibs.2017.01.001 Text en © 2017 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Opinion Martens, Lennart Vizcaíno, Juan Antonio A Golden Age for Working with Public Proteomics Data |
title | A Golden Age for Working with Public Proteomics Data |
title_full | A Golden Age for Working with Public Proteomics Data |
title_fullStr | A Golden Age for Working with Public Proteomics Data |
title_full_unstemmed | A Golden Age for Working with Public Proteomics Data |
title_short | A Golden Age for Working with Public Proteomics Data |
title_sort | golden age for working with public proteomics data |
topic | Opinion |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5414595/ https://www.ncbi.nlm.nih.gov/pubmed/28118949 http://dx.doi.org/10.1016/j.tibs.2017.01.001 |
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