Knowledge-based technologies in proteomics

被引:0
|
作者
E. A. Ponomarenko
E. V. Ilgisonis
A. V. Lisitsa
机构
[1] Russian Academy of Medical Sciences,Institute of Biomedical Chemistry
[2] Russian Academy of Sciences,Engelhardt Institute of Molecular Biology
来源
Russian Journal of Bioorganic Chemistry | 2011年 / 37卷
关键词
knowledgebase; metabolic pathway; gene ontology; mass-spectrometry;
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摘要
Proteomic technologies enable one to identify thousands of proteins in biological samples. These data require appropriate means for storage, dissemination and analytical processing to decipher the new knowledge. Automatic processing of high-efficient experimental results is powered by the controlled vocabularies, such as Medical Subject Headings and GeneOntology. While ontology and vocabularies undergo constant evolution, it is necessary to provide centralized storage of proteomic data for further revision in accordance with the updated knowledge domain. Proteomic repositories like PRIDE, The Global Proteome Machine, PeptideAtlas, etc., are available to harbor the wealth of mass spectral data and appropriate protein identifications. The existing repositories facilitate the development of knowledge extraction technologies to compare the list of identified proteins with the GeneOntology annotations, Medical Subject Headings, metabolic and regulatory pathways. This paper reviews modern analytical tools that exploit the knowledge-based technologies for proteome research.
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