The PRIDE database resources in 2022: a hub for mass spectrometry-based proteomics evidences.
The PRIDE database resources in 2022: a hub for mass spectrometry-based proteomics evidences.
复制标题
2022年的PRIDE数据库资源：基于质谱的蛋白质组学证据的中心。
DOI：
10.1093/nar/gkab1038
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发表时间：
2022-01-07
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;Bai J;Bandla C;García-Seisdedos D;Hewapathirana S;Kamatchinathan S;Kundu DJ;Prakash A;Frericks-Zipper A;Eisenacher M;Walzer M;Wang S;Brazma A;Vizcaíno JA
蛋白质组学识别（PRIDE）数据库（https://www.ebi.ac.uk/pride/）是世界上最大的基于质谱的蛋白质组学数据的数据存储库。 ）联盟和核心核心数据资源。 2019年。骄傲档案（Pride）提交的数据集数量（Pride的档案部分）平均每月达到约500个数据集。除了不断改进Pride Archive数据管道和基础架构外，Pride Spectra Archive还开发了使用通用频谱标识符直接访问提交的质谱。为了改善样本元素注释，已开发出来。进入其他添加值资源，例如Uniprot，Ensembl和Expression Atlas。
The PRoteomics IDEntifications (PRIDE) database (https://www.ebi.ac.uk/pride/) is the world's largest data repository of mass spectrometry-based proteomics data. PRIDE is one of the founding members of the global ProteomeXchange (PX) consortium and an ELIXIR core data resource. 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 2019. The number of submitted datasets to PRIDE Archive (the archival component of PRIDE) has reached on average around 500 datasets per month during 2021. In addition to continuous improvements in PRIDE Archive data pipelines and infrastructure, the PRIDE Spectra Archive has been developed to provide direct access to the submitted mass spectra using Universal Spectrum Identifiers. As a key point, the file format MAGE-TAB for proteomics has been developed to enable the improvement of sample metadata annotation. Additionally, the resource PRIDE Peptidome provides access to aggregated peptide/protein evidences across PRIDE Archive. Furthermore, we will describe how PRIDE has increased its efforts to reuse and disseminate high-quality proteomics data into other added-value resources such as UniProt, Ensembl and Expression Atlas.
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影响因子：
14.9
作者：
Gostev M;Faulconbridge A;Brandizi M;Fernandez-Banet J;Sarkans U;Brazma A;Parkinson H
通讯作者：
Parkinson H
影响因子：
48
作者：
Choi M;Carver J;Chiva C;Tzouros M;Huang T;Tsai TH;Pullman B;Bernhardt OM;Hüttenhain R;Teo GC;Perez-Riverol Y;Muntel J;Müller M;Goetze S;Pavlou M;Verschueren E;Wollscheid B;Nesvizhskii AI;Reiter L;Dunkley T;Sabidó E;Bandeira N;Vitek O
通讯作者：
Vitek O
影响因子：
14.9
作者：
Ma J;Chen T;Wu S;Yang C;Bai M;Shu K;Li K;Zhang G;Jin Z;He F;Hermjakob H;Zhu Y
通讯作者：
Zhu Y
影响因子：
14.9
作者：
Moriya Y;Kawano S;Okuda S;Watanabe Y;Matsumoto M;Takami T;Kobayashi D;Yamanouchi Y;Araki N;Yoshizawa AC;Tabata T;Iwasaki M;Sugiyama N;Tanaka S;Goto S;Ishihama Y
通讯作者：
Ishihama Y
影响因子：
14.9
作者：
Harrison PW;Lopez R;Rahman N;Allen SG;Aslam R;Buso N;Cummins C;Fathy Y;Felix E;Glont M;Jayathilaka S;Kadam S;Kumar M;Lauer KB;Malhotra G;Mosaku A;Edbali O;Park YM;Parton A;Pearce M;Estrada Pena JF;Rossetto J;Russell C;Selvakumar S;Sitjà XP;Sokolov A;Thorne R;Ventouratou M;Walter P;Yordanova G;Zadissa A;Cochrane G;Blomberg N;Apweiler R
通讯作者：
Apweiler R