The PRIDE database and related tools and resources in 2019: improving support for quantification data.
The PRIDE database and related tools and resources in 2019: improving support for quantification data.
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DOI:
10.1093/nar/gky1106
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发表时间:
2019-01-08
影响因子:
14.9
通讯作者:
Vizcaíno JA
中科院分区:
文献类型:
--
作者:
Perez-Riverol Y;Csordas A;Bai J;Bernal-Llinares M;Hewapathirana S;Kundu DJ;Inuganti A;Griss J;Mayer G;Eisenacher M;Pérez E;Uszkoreit J;Pfeuffer J;Sachsenberg T;Yilmaz S;Tiwary S;Cox J;Audain E;Walzer M;Jarnuczak AF;Ternent T;Brazma A;Vizcaíno JA
The PRoteomics IDEntifications (PRIDE) database (https://www.ebi.ac.uk/pride/) is the world’s largest data repository of mass spectrometry-based proteomics data, and is one of the founding members of the global ProteomeXchange (PX) consortium. In this manuscript, we summarize the developments in PRIDE resources and related tools since the previous update manuscript was published in Nucleic Acids Research in 2016. In the last 3 years, public data sharing through PRIDE (as part of PX) has definitely become the norm in the field. In parallel, data re-use of public proteomics data has increased enormously, with multiple applications. We first describe the new architecture of PRIDE Archive, the archival component of PRIDE. PRIDE Archive and the related data submission framework have been further developed to support the increase in submitted data volumes and additional data types. A new scalable and fault tolerant storage backend, Application Programming Interface and web interface have been implemented, as a part of an ongoing process. Additionally, we emphasize the improved support for quantitative proteomics data through the mzTab format. At last, we outline key statistics on the current data contents and volume of downloads, and how PRIDE data are starting to be disseminated to added-value resources including Ensembl, UniProt and Expression Atlas.
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影响因子:
3.4
作者:
Perez-Riverol Y;Vizcaíno JA;Griss J
通讯作者:
Griss J
DOI:
10.1093/bioinformatics/btx192
发表时间:
2017-08-15
期刊:
Bioinformatics (Oxford, England)
影响因子:
--
作者:
da Veiga Leprevost F;Grüning BA;Alves Aflitos S;Röst HL;Uszkoreit J;Barsnes H;Vaudel M;Moreno P;Gatto L;Weber J;Bai M;Jimenez RC;Sachsenberg T;Pfeuffer J;Vera Alvarez R;Griss J;Nesvizhskii AI;Perez-Riverol Y
通讯作者:
Perez-Riverol Y
DOI:
10.1093/bioinformatics/btv250
发表时间:
2015-09-01
期刊:
Bioinformatics (Oxford, England)
影响因子:
--
作者:
Perez-Riverol Y;Uszkoreit J;Sanchez A;Ternent T;Del Toro N;Hermjakob H;Vizcaíno JA;Wang R
通讯作者:
Wang R
影响因子:
14.9
作者:
Okuda S;Watanabe Y;Moriya Y;Kawano S;Yamamoto T;Matsumoto M;Takami T;Kobayashi D;Araki N;Yoshizawa AC;Tabata T;Sugiyama N;Goto S;Ishihama Y
通讯作者:
Ishihama Y
影响因子:
14.9
作者:
Deutsch EW;Csordas A;Sun Z;Jarnuczak A;Perez-Riverol Y;Ternent T;Campbell DS;Bernal-Llinares M;Okuda S;Kawano S;Moritz RL;Carver JJ;Wang M;Ishihama Y;Bandeira N;Hermjakob H;Vizcaíno JA
通讯作者:
Vizcaíno JA