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Version 4.0 of PaxDb: Protein abundance data, integrated across model organisms, tissues, and cell‐lines

Protein quantification at proteome‐wide scale is an important aim, enabling insights into fundamental cellular biology and serving to constrain experiments and theoretical models. While proteome‐wide quantification is not yet fully routine, many datasets approaching proteome‐wide coverage are becomi...

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Autores principales: Wang, Mingcong, Herrmann, Christina J., Simonovic, Milan, Szklarczyk, Damian, von Mering, Christian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6680238/
https://www.ncbi.nlm.nih.gov/pubmed/25656970
http://dx.doi.org/10.1002/pmic.201400441
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author Wang, Mingcong
Herrmann, Christina J.
Simonovic, Milan
Szklarczyk, Damian
von Mering, Christian
author_facet Wang, Mingcong
Herrmann, Christina J.
Simonovic, Milan
Szklarczyk, Damian
von Mering, Christian
author_sort Wang, Mingcong
collection PubMed
description Protein quantification at proteome‐wide scale is an important aim, enabling insights into fundamental cellular biology and serving to constrain experiments and theoretical models. While proteome‐wide quantification is not yet fully routine, many datasets approaching proteome‐wide coverage are becoming available through biophysical and MS techniques. Data of this type can be accessed via a variety of sources, including publication supplements and online data repositories. However, access to the data is still fragmentary, and comparisons across experiments and organisms are not straightforward. Here, we describe recent updates to our database resource “PaxDb” (Protein Abundances Across Organisms). PaxDb focuses on protein abundance information at proteome‐wide scope, irrespective of the underlying measurement technique. Quantification data is reprocessed, unified, and quality‐scored, and then integrated to build a meta‐resource. PaxDb also allows evolutionary comparisons through precomputed gene orthology relations. Recently, we have expanded the scope of the database to include cell‐line samples, and more systematically scan the literature for suitable datasets. We report that a significant fraction of published experiments cannot readily be accessed and/or parsed for quantitative information, requiring additional steps and efforts. The current update brings PaxDb to 414 datasets in 53 organisms, with (semi‐) quantitative abundance information covering more than 300 000 proteins.
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spelling pubmed-66802382019-08-09 Version 4.0 of PaxDb: Protein abundance data, integrated across model organisms, tissues, and cell‐lines Wang, Mingcong Herrmann, Christina J. Simonovic, Milan Szklarczyk, Damian von Mering, Christian Proteomics Technical Brief Protein quantification at proteome‐wide scale is an important aim, enabling insights into fundamental cellular biology and serving to constrain experiments and theoretical models. While proteome‐wide quantification is not yet fully routine, many datasets approaching proteome‐wide coverage are becoming available through biophysical and MS techniques. Data of this type can be accessed via a variety of sources, including publication supplements and online data repositories. However, access to the data is still fragmentary, and comparisons across experiments and organisms are not straightforward. Here, we describe recent updates to our database resource “PaxDb” (Protein Abundances Across Organisms). PaxDb focuses on protein abundance information at proteome‐wide scope, irrespective of the underlying measurement technique. Quantification data is reprocessed, unified, and quality‐scored, and then integrated to build a meta‐resource. PaxDb also allows evolutionary comparisons through precomputed gene orthology relations. Recently, we have expanded the scope of the database to include cell‐line samples, and more systematically scan the literature for suitable datasets. We report that a significant fraction of published experiments cannot readily be accessed and/or parsed for quantitative information, requiring additional steps and efforts. The current update brings PaxDb to 414 datasets in 53 organisms, with (semi‐) quantitative abundance information covering more than 300 000 proteins. John Wiley and Sons Inc. 2015-03-12 2015-09 /pmc/articles/PMC6680238/ /pubmed/25656970 http://dx.doi.org/10.1002/pmic.201400441 Text en © 2015 The Authors. PROTEOMICS published by Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Technical Brief
Wang, Mingcong
Herrmann, Christina J.
Simonovic, Milan
Szklarczyk, Damian
von Mering, Christian
Version 4.0 of PaxDb: Protein abundance data, integrated across model organisms, tissues, and cell‐lines
title Version 4.0 of PaxDb: Protein abundance data, integrated across model organisms, tissues, and cell‐lines
title_full Version 4.0 of PaxDb: Protein abundance data, integrated across model organisms, tissues, and cell‐lines
title_fullStr Version 4.0 of PaxDb: Protein abundance data, integrated across model organisms, tissues, and cell‐lines
title_full_unstemmed Version 4.0 of PaxDb: Protein abundance data, integrated across model organisms, tissues, and cell‐lines
title_short Version 4.0 of PaxDb: Protein abundance data, integrated across model organisms, tissues, and cell‐lines
title_sort version 4.0 of paxdb: protein abundance data, integrated across model organisms, tissues, and cell‐lines
topic Technical Brief
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6680238/
https://www.ncbi.nlm.nih.gov/pubmed/25656970
http://dx.doi.org/10.1002/pmic.201400441
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