Literature DB >> 16222422

A bioinformatics perspective on proteomics: data storage, analysis, and integration.

Andreas Kremer1, Reinhard Schneider, Georg C Terstappen.   

Abstract

The field of proteomics is advancing rapidly as a result of powerful new technologies and proteomics experiments yield a vast and increasing amount of information. Data regarding protein occurrence, abundance, identity, sequence, structure, properties, and interactions need to be stored. Currently, a common standard has not yet been established and open access to results is needed for further development of robust analysis algorithms. Databases for proteomics will evolve from pure storage into knowledge resources, providing a repository for information (meta-data) which is mainly not stored in simple flat files. This review will shed light on recent steps towards the generation of a common standard in proteomics data storage and integration, but is not meant to be a comprehensive overview of all available databases and tools in the proteomics community.

Mesh:

Year:  2005        PMID: 16222422     DOI: 10.1007/s10540-005-2850-4

Source DB:  PubMed          Journal:  Biosci Rep        ISSN: 0144-8463            Impact factor:   3.840


  4 in total

1.  Discovery of a set of biomarkers of human lung adenocarcinoma through cell-map proteomics and bioinformatics.

Authors:  Yandong Nan; Faguang Jin; Shuanying Yang; Yingxuan Tian; Yonghong Xie; Enqing Fu; Hong Yu
Journal:  Med Oncol       Date:  2009-12-30       Impact factor: 3.064

2.  Analysing protein-protein interaction networks of human liver cancer cell lines with diverse metastasis potential.

Authors:  Hai-Jun Zhou; Yin-Kun Liu; Zhuozhe Li; Dong Yun; Qiang-Ling Shun; Kun Guo
Journal:  J Cancer Res Clin Oncol       Date:  2007-04-26       Impact factor: 4.553

Review 3.  Toxoplasma gondii proteomics.

Authors:  Louis M Weiss; Andras Fiser; Ruth Hogue Angeletti; Kami Kim
Journal:  Expert Rev Proteomics       Date:  2009-06       Impact factor: 3.940

4.  Francisella tularensis novicida proteomic and transcriptomic data integration and annotation based on semantic web technologies.

Authors:  Nadia Anwar; Ela Hunt
Journal:  BMC Bioinformatics       Date:  2009-10-01       Impact factor: 3.169

  4 in total

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