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      Plasma Proteome Database as a resource for proteomics research: 2014 update

      research-article
      1 , 2 , 1 , 2 , 1 , 1 , 3 , 1 , 4 , 5 , 1 , 1 , 6 , 1 , 1 , 7 , 7 , 8 , 9 , 1 , 3 , 4 , 10 , 11 , 5 , 12 , 1 , 1 , 1 , 4 , 12 , 1 , 13 , 14 , 15 , 16 , * , 1 , 2 , 3 , *
      Nucleic Acids Research
      Oxford University Press

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          Abstract

          Plasma Proteome Database (PPD; http://www.plasmaproteomedatabase.org/) was initially described in the year 2005 as a part of Human Proteome Organization’s (HUPO’s) pilot initiative on Human Plasma Proteome Project. Since then, improvements in proteomic technologies and increased throughput have led to identification of a large number of novel plasma proteins. To keep up with this increase in data, we have significantly enriched the proteomic information in PPD. This database currently contains information on 10 546 proteins detected in serum/plasma of which 3784 have been reported in two or more studies. The latest version of the database also incorporates mass spectrometry-derived data including experimentally verified proteotypic peptides used for multiple reaction monitoring assays. Other novel features include published plasma/serum concentrations for 1278 proteins along with a separate category of plasma-derived extracellular vesicle proteins. As plasma proteins have become a major thrust in the field of biomarkers, we have enabled a batch-based query designated Plasma Proteome Explorer, which will permit the users in screening a list of proteins or peptides against known plasma proteins to assess novelty of their data set. We believe that PPD will facilitate both clinical and basic research by serving as a comprehensive reference of plasma proteins in humans and accelerate biomarker discovery and translation efforts.

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          The Proteomics Identifications (PRIDE) database and associated tools: status in 2013

          The PRoteomics IDEntifications (PRIDE, http://www.ebi.ac.uk/pride) database at the European Bioinformatics Institute is one of the most prominent data repositories of mass spectrometry (MS)-based proteomics data. Here, we summarize recent developments in the PRIDE database and related tools. First, we provide up-to-date statistics in data content, splitting the figures by groups of organisms and species, including peptide and protein identifications, and post-translational modifications. We then describe the tools that are part of the PRIDE submission pipeline, especially the recently developed PRIDE Converter 2 (new submission tool) and PRIDE Inspector (visualization and analysis tool). We also give an update about the integration of PRIDE with other MS proteomics resources in the context of the ProteomeXchange consortium. Finally, we briefly review the quality control efforts that are ongoing at present and outline our future plans.
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            Update on activities at the Universal Protein Resource (UniProt) in 2013

            The mission of the Universal Protein Resource (UniProt) (http://www.uniprot.org) is to support biological research by providing a freely accessible, stable, comprehensive, fully classified, richly and accurately annotated protein sequence knowledgebase. It integrates, interprets and standardizes data from numerous resources to achieve the most comprehensive catalogue of protein sequences and functional annotation. UniProt comprises four major components, each optimized for different uses, the UniProt Archive, the UniProt Knowledgebase, the UniProt Reference Clusters and the UniProt Metagenomic and Environmental Sequence Database. UniProt is produced by the UniProt Consortium, which consists of groups from the European Bioinformatics Institute (EBI), the SIB Swiss Institute of Bioinformatics (SIB) and the Protein Information Resource (PIR). UniProt is updated and distributed every 4 weeks and can be accessed online for searches or downloads.
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              Protein typing of circulating microvesicles allows real-time monitoring of glioblastoma therapy.

              Glioblastomas shed large quantities of small, membrane-bound microvesicles into the circulation. Although these hold promise as potential biomarkers of therapeutic response, their identification and quantification remain challenging. Here, we describe a highly sensitive and rapid analytical technique for profiling circulating microvesicles directly from blood samples of patients with glioblastoma. Microvesicles, introduced onto a dedicated microfluidic chip, are labeled with target-specific magnetic nanoparticles and detected by a miniaturized nuclear magnetic resonance system. Compared with current methods, this integrated system has a much higher detection sensitivity and can differentiate glioblastoma multiforme (GBM) microvesicles from nontumor host cell-derived microvesicles. We also show that circulating GBM microvesicles can be used to analyze primary tumor mutations and as a predictive metric of treatment-induced changes. This platform could provide both an early indicator of drug efficacy and a potential molecular stratifier for human clinical trials.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                January 2014
                3 December 2013
                3 December 2013
                : 42
                : D1 , Database issue
                : D959-D965
                Affiliations
                1Institute of Bioinformatics, International Technology Park, Bangalore 560 066, Karnataka, India, 2Amrita School of Biotechnology, Amrita University, Kollam 690 525, Kerala, India, 3Centre of Excellence in Bioinformatics, School of Life Sciences, Pondicherry University, Puducherry 605 014, India, 4Department of Biochemistry and Molecular Biology, Pondicherry University, Puducherry 605014, India, 5Department of Neurochemistry, National Institute of Mental Health and Neurosciences, Bangalore 560 022, Karnataka, India, 6Department of Biotechnology, Kuvempu University, Shankaraghatta 577 451, Karnataka, India, 7Government Medical College, Bhavnagar 364 001, Gujarat, India, 8Mahatma Gandhi Institute of Medical Sciences, Sevagram, Wardha 442 012, Maharashtra, India, 9The Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA, 10Department of Internal Medicine, Armed Forces Medical College, Pune 411 040, Maharashtra, India, 11Department of Neurology, National Institute of Mental Health and Neurosciences, Bangalore 560 022, Karnataka, India, 12Department of Biochemistry, La Trobe Institute for Molecular Science, La Trobe University, Melbourne, Victoria 3084, Australia, 13McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, MD 21205, USA, 14Department of Biological Chemistry, Johns Hopkins University, Baltimore, MD 21205, USA, 15Department of Oncology, Johns Hopkins University, Baltimore, MD 21205, USA and 16Department of Pathology, Johns Hopkins University, Baltimore, MD 21205, USA
                Author notes
                *To whom correspondence should be addressed. Tel: +410 502 6662; Fax: +410 502 7544; Email: pandey@ 123456jhmi.edu
                Correspondence may also be addressed to T. S. Keshava Prasad. Tel: +080 28416140; Fax: +28416132; Email: keshav@ 123456ibioinformatics.org

                Present address: Dindagur Nagaraja, Dharwad Institute of Mental Health and Neuro Sciences (DIMHANS), Dharwad, Karnataka, India.

                Article
                gkt1251
                10.1093/nar/gkt1251
                3965042
                24304897
                4fb4923e-9f0c-4066-8e9e-256189e9f579
                © The Author(s) 2013. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/3.0/), 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@oup.com

                History
                : 16 August 2013
                : 10 November 2013
                : 11 November 2013
                Page count
                Pages: 7
                Categories
                V. Human genome, model organisms, comparative genomics
                Custom metadata
                1 January 2014

                Genetics
                Genetics

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