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      iProX: an integrated proteome resource

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          Abstract

          Sharing of research data in public repositories has become best practice in academia. With the accumulation of massive data, network bandwidth and storage requirements are rapidly increasing. The ProteomeXchange (PX) consortium implements a mode of centralized metadata and distributed raw data management, which promotes effective data sharing. To facilitate open access of proteome data worldwide, we have developed the integrated proteome resource iProX ( http://www.iprox.org) as a public platform for collecting and sharing raw data, analysis results and metadata obtained from proteomics experiments. The iProX repository employs a web-based proteome data submission process and open sharing of mass spectrometry-based proteomics datasets. Also, it deploys extensive controlled vocabularies and ontologies to annotate proteomics datasets. Users can use a GUI to provide and access data through a fast Aspera-based transfer tool. iProX is a full member of the PX consortium; all released datasets are freely accessible to the public. iProX is based on a high availability architecture and has been deployed as part of the proteomics infrastructure of China, ensuring long-term and stable resource support. iProX will facilitate worldwide data analysis and sharing of proteomics experiments.

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          BRENDA in 2017: new perspectives and new tools in BRENDA

          The BRENDA enzyme database (www.brenda-enzymes.org) has developed into the main enzyme and enzyme-ligand information system in its 30 years of existence. The information is manually extracted from primary literature and extended by text mining procedures, integration of external data and prediction algorithms. Approximately 3 million data from 83 000 enzymes and 137 000 literature references constitute the manually annotated core. Text mining procedures extend these data with information on occurrence, enzyme-disease relationships and kinetic data. Prediction algorithms contribute locations and genome annotations. External data and links complete the data with sequences and 3D structures. A total of 206 000 enzyme ligands provide functional and structural data. BRENDA offers a complex query tool engine allowing the users an efficient access to the data via different search methods and explorers. The new design of the BRENDA entry page and the enzyme summary pages improves the user access and the performance. New interactive and intuitive BRENDA pathway maps give an overview on biochemical processes and facilitate the visualization of enzyme, ligand and organism information in the biochemical context. SCOPe and CATH, databases for protein structure classification, are included. New online and video tutorials provide online training for the users. BRENDA is freely available for academic users.
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            Discovering and linking public omics data sets using the Omics Discovery Index

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              The PSI-MOD community standard for representation of protein modification data.

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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                08 January 2019
                25 September 2018
                25 September 2018
                : 47
                : Database issue , Database issue
                : D1211-D1217
                Affiliations
                [1 ]State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Life Omics, Beijing 102206, China
                [2 ]Chongqing University of Posts and Telecommunications, Chongqing 400065, China
                [3 ]National Supercomputing Center in Changsha, Hunan University, Changsha 410082, China
                [4 ]Shanghai Center for Bioinformation Technology, Shanghai Institutes of Biomedicine, Shanghai Academy of Science and Technology, Shanghai 200235, China
                [5 ]Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China
                [6 ]European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
                Author notes
                To whom correspondence should be addressed. Tel: +86 10 61777058; Fax: +86 10 61777058; Email: zhuyunping@ 123456gmail.com . Correspondence may also be addressed to Fuchu He. Email: hefc@ 123456nic.bmi.ac.cn . Correspondence may also be addressed to Henning Hermjakob. Email: hhe@ 123456ebi.ac.uk

                The authors wish it to be known that, in their opinion, the first two authors should be regarded as Joint First Authors.

                Author information
                http://orcid.org/0000-0002-8934-922X
                Article
                gky869
                10.1093/nar/gky869
                6323926
                30252093
                6e9bffe6-d411-4dcf-8763-325a98602c55
                © The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@ 123456oup.com

                History
                : 14 September 2018
                : 9 September 2018
                : 14 August 2018
                Page count
                Pages: 7
                Funding
                Funded by: National Key Research Program of China
                Award ID: 2016YFC0901701
                Award ID: 2016YFB0201702
                Award ID: 2016YFC0901601
                Funded by: International Scientific and Technological Cooperation project of China
                Award ID: 2014DFB30010
                Award ID: 2014DFB30030
                Funded by: National High Technology Research and Development Program of China
                Award ID: 2015AA020108
                Funded by: National Science Foundation of China 10.13039/501100001809
                Award ID: 21475150
                Funded by: Biotechnology and Biological Sciences Research Council 10.13039/501100000268
                Award ID: BB/N022432/1
                Categories
                Database Issue

                Genetics
                Genetics

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