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  Molecular interaction networks in the analyses of sequence variation and proteomics data

Stelzl, U. (2013). Molecular interaction networks in the analyses of sequence variation and proteomics data. PROTEOMICS CLINICAL APPLICATIONS, 7(11-12), 727-732. doi:10.1002/prca.201300039.

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© 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
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 Creators:
Stelzl, Ulrich1, Author           
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1Molecular Interaction Networks (Ulrich Stelzl), Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1479660              

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Free keywords: Genetic variation; MS; Phosphorylation; Posttranslational modification; Protein–protein interactions; Yeast two-hybrid
 Abstract: Protein-protein interaction networks are typically generated in standard cell lines or model organisms as it is prohibitively difficult to record large interaction datasets from specific tissues or disease models at a reasonable pace. Although the interaction data are of high confidence, they thus do not reflect in vivo relationships as such. A wealth of physiologically relevant protein information, obtained under different conditions and from different systems, is available including information on genetic variation, protein levels, and PTMs. However, these data are difficult to assess comprehensively because the relationships between the entities remain elusive from the measurements. Here, we exemplarily highlight recent studies that gained deeper insight from genetic variation, protein, and PTM measurements using interaction information pointing toward the importance and potential of interaction networks for the interpretation of sequencing and proteomics data.

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Language(s): eng - English
 Dates: 2013-10-292013-12
 Publication Status: Issued
 Pages: -
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1002/prca.201300039
ISSN: 1862-8354 (Electronic)1862-8346 (Print)
URI: http://www.ncbi.nlm.nih.gov/pubmed/24039079
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Title: PROTEOMICS CLINICAL APPLICATIONS
  Other : Proteom. Clin. Appl.
Source Genre: Journal
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Pages: - Volume / Issue: 7 (11-12) Sequence Number: - Start / End Page: 727 - 732 Identifier: ISSN: 1862-8346
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000277300