Literature DB >> 15966823

New approaches towards integrated proteomic databases and depositories.

Christian Rohlff1.   

Abstract

Since the publication of the human genome, two key points have emerged. First, it is still not certain which regions of the genome code for proteins. Second, the number of discrete protein-coding genes is far fewer than the number of different proteins. Proteomics has the potential to address some of these postgenomic issues if the obstacles that we face can be overcome in our efforts to combine proteomic and genomic data. There are many challenges associated with high-throughput and high-output proteomic technologies. Consequently, for proteomics to continue at its current growth rate, new approaches must be developed to ease data management and data mining. Initiatives have been launched to develop standard data formats for exchanging mass spectrometry proteomic data, including the Proteomics Standards Initiative formed by the Human Proteome Organization. Databases such as SwissProt and Uniprot are publicly available repositories for protein sequences annotated for function, subcellular location and known potential post-translational modifications. The availability of bioinformatics solutions is crucial for proteomics technologies to fulfil their promise of adding further definition to the functional output of the human genome. The aim of the Oxford Genome Anatomy Project is to provide a framework for integrating molecular, cellular, phenotypic and clinical information with experimental genetic and proteomics data. This perspective also discusses models to make the Oxford Genome Anatomy Project accessible and beneficial for academic and commercial research and development.

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Year:  2004        PMID: 15966823     DOI: 10.1586/14789450.1.3.267

Source DB:  PubMed          Journal:  Expert Rev Proteomics        ISSN: 1478-9450            Impact factor:   3.940


  2 in total

1.  Circulating Glycan Monosaccharide Composite-Based Biomarker Diagnoses Colorectal Cancer at Early Stages and Predicts Prognosis.

Authors:  Haoran Li; Xueling Wang; Xiaodan Huang; Yanli He; Yiran Zhang; Cui Hao; Pengjiao Zeng; Meng Zhang; Yanyun Gao; Dandan Yang; Ming Shan; Huaiqian Dou; Xiaoyu Li; Xiaotian Chang; Zibin Tian; Lijuan Zhang
Journal:  Front Oncol       Date:  2022-04-29       Impact factor: 5.738

2.  PRODIS: a proteomics data management system with support to experiment tracking.

Authors:  Alessandra Faria-Campos; Herbert Fernandes-Rausch; Celina Val; Peter Thorun; Vinicius Abreu; Paulo Henrique Batista; Paulo Henrique Mendonça; Vinicius Alves; Maíra Ribeiro Rodrigues; Adriano Pimenta; Glória Franco; Sérgio Vale Aguiar Campos
Journal:  BMC Genomics       Date:  2011-12-22       Impact factor: 3.969

  2 in total

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