Linked Life Data

15188397

Source:http://linkedlifedata.com/resource/pubmed/id/15188397

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
5
pubmed:dateCreated
2004-6-9
pubmed:abstractText
The analysis of proteomes of biological organisms represents a major challenge of the post-genome era. Classical proteomics combines two-dimensional electrophoresis (2-DE) and mass spectrometry (MS) for the identification of proteins. Novel technologies such as isotope coded affinity tag (ICAT)-liquid chromatography/mass spectrometry (LC/MS) open new insights into protein alterations. The vast amount and diverse types of proteomic data require adequate web-accessible computational and database technologies for storage, integration, dissemination, analysis and visualization. A proteome database system (http://www.mpiib-berlin.mpg.de/2D-PAGE) for microbial research has been constructed which integrates 2-DE/MS, ICAT-LC/MS and functional classification data of proteins with genomic, metabolic and other biological knowledge sources. The two-dimensional polyacrylamide gel electrophoresis database delivers experimental data on microbial proteins including mass spectra for the validation of protein identification. The ICAT-LC/MS database comprises experimental data for protein alterations of mycobacterial strains BCG vs. H37Rv. By formulating complex queries within a functional protein classification database "FUNC_CLASS" for Mycobacterium tuberculosis and Helicobacter pylori the researcher can gather precise information on genes, proteins, protein classes and metabolic pathways. The use of the R language in the database architecture allows high-level data analysis and visualization to be performed "on-the-fly". The database system is centrally administrated, and investigators without specific bioinformatic competence in database construction can submit their data. The database system also serves as a template for a prototype of a European Proteome Database of Pathogenic Bacteria. Currently, the database system includes proteome information for six strains of microorganisms.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
May
pubmed:issn
1615-9853
pubmed:author
pubmed:issnType
Print
pubmed:volume
4
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1305-13
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2004
pubmed:articleTitle
Web-accessible proteome databases for microbial research.
pubmed:affiliation
Max Planck Institute for Infection Biology, Berlin, Germany.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't