title: [Knowledge-based technologies in proteomics].
abstract: Proteomic technologies enable 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 experiment results is powered by the controlled vocabularies, such as Medical Subjects Headings and GeneOntology. While ontology and vocabularies undergo constant evolution, it is necessary to provide the 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 Subjects Headings, metabolic and regulatory pathways. This paper reviews modern analytical tools that exploit the knowledge-based technologies for proteome research.
authors: E A
authors: EA
authors: Ponomarenko
authors: E V
authors: EV
authors: Il'gisonis
authors: A V
authors: AV
authors: Lisitsa
mesh_terms: D000818:Animals; D045424:Complex Mixtures / Q000737:chemistry*; D019295:Computational Biology; D006801:Humans; D033181:Information Dissemination; D016247:Information Storage and Retrieval; D051188:Knowledge Bases; D013058:Mass Spectrometry; D046650:Medical Subject Headings; D011506:Proteins / Q000032:analysis*; D040901:Proteomics / Q000379:methods; D012984:Software / Q000639:trends
chemical_list: D045424:Complex Mixtures; D011506:Proteins