001     8400
005     20200402205800.0
024 7 _ |2 pmid
|a pmid:19798668
024 7 _ |2 pmc
|a pmc:PMC3076061
024 7 _ |2 DOI
|a 10.1002/pmic.200900259
024 7 _ |2 WOS
|a WOS:000273393900006
024 7 _ |2 ISSN
|a 1615-9861
024 7 _ |a altmetric:6070985
|2 altmetric
037 _ _ |a PreJuSER-8400
041 _ _ |a eng
082 _ _ |a 540
084 _ _ |2 WoS
|a Biochemical Research Methods
084 _ _ |2 WoS
|a Biochemistry & Molecular Biology
100 1 _ |0 P:(DE-HGF)0
|a Qi, Y.
|b 0
245 _ _ |a Systematic prediction of human membrane receptor interactions
260 _ _ |a Weinheim
|b Wiley VCH
|c 2009
300 _ _ |a 5243 - 5255
336 7 _ |a Journal Article
|0 PUB:(DE-HGF)16
|2 PUB:(DE-HGF)
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|0 0
|2 EndNote
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a article
|2 DRIVER
440 _ 0 |0 10401
|a Proteomics
|v 9
|x 1615-9853
|y 23
500 _ _ |a This work was supported in part by National Science Foundation Grants ITR 0225656, CAREER 0448453 and CAREER CC044917, National Institutes of Health Grants NLM108730, R01 CA098372 and AI060422 and the Sofya Kovalvskaya Award (to J. K. S.) from the Humboldt Foundation.
520 _ _ |a Membrane receptor-activated signal transduction pathways are integral to cellular functions and disease mechanisms in humans. Identification of the full set of proteins interacting with membrane receptors by high-throughput experimental means is difficult because methods to directly identify protein interactions are largely not applicable to membrane proteins. Unlike prior approaches that attempted to predict the global human interactome, we used a computational strategy that only focused on discovering the interacting partners of human membrane receptors leading to improved results for these proteins. We predict specific interactions based on statistical integration of biological data containing highly informative direct and indirect evidences together with feedback from experts. The predicted membrane receptor interactome provides a system-wide view, and generates new biological hypotheses regarding interactions between membrane receptors and other proteins. We have experimentally validated a number of these interactions. The results suggest that a framework of systematically integrating computational predictions, global analyses, biological experimentation and expert feedback is a feasible strategy to study the human membrane receptor interactome.
536 _ _ |0 G:(DE-Juel1)FUEK443
|2 G:(DE-HGF)
|a Programm Biosoft
|c N03
|x 0
588 _ _ |a Dataset connected to Web of Science, Pubmed
650 _ 2 |2 MeSH
|a Computational Biology: methods
650 _ 2 |2 MeSH
|a Humans
650 _ 2 |2 MeSH
|a Protein Interaction Mapping: methods
650 _ 2 |2 MeSH
|a Proteome: analysis
650 _ 2 |2 MeSH
|a Proteome: metabolism
650 _ 2 |2 MeSH
|a Proteomics: methods
650 _ 2 |2 MeSH
|a Receptor, Epidermal Growth Factor: analysis
650 _ 2 |2 MeSH
|a Receptor, Epidermal Growth Factor: metabolism
650 _ 2 |2 MeSH
|a Receptors, Cell Surface: analysis
650 _ 2 |2 MeSH
|a Receptors, Cell Surface: metabolism
650 _ 2 |2 MeSH
|a Signal Transduction
650 _ 2 |2 MeSH
|a Systems Biology: methods
650 _ 7 |0 0
|2 NLM Chemicals
|a Proteome
650 _ 7 |0 0
|2 NLM Chemicals
|a Receptors, Cell Surface
650 _ 7 |0 EC 2.7.10.1
|2 NLM Chemicals
|a EGFR protein, human
650 _ 7 |0 EC 2.7.10.1
|2 NLM Chemicals
|a Receptor, Epidermal Growth Factor
650 _ 7 |2 WoSType
|a J
653 2 0 |2 Author
|a Data integration
653 2 0 |2 Author
|a Membrane proteins
653 2 0 |2 Author
|a Protein-protein interaction network
653 2 0 |2 Author
|a Receptor interactome
653 2 0 |2 Author
|a Receptor crosstalk
653 2 0 |2 Author
|a Signal transcluction
653 2 0 |2 Author
|a Systems biology
700 1 _ |0 P:(DE-HGF)0
|a Dhiman, H.K.
|b 1
700 1 _ |0 P:(DE-HGF)0
|a Bhola, N.E.
|b 2
700 1 _ |0 P:(DE-HGF)0
|a Budyak, I.
|b 3
700 1 _ |0 P:(DE-HGF)0
|a Kar, S.
|b 4
700 1 _ |0 P:(DE-HGF)0
|a Man, D.
|b 5
700 1 _ |0 P:(DE-HGF)0
|a Dutta, A.
|b 6
700 1 _ |0 P:(DE-HGF)0
|a Tirupula, K.
|b 7
700 1 _ |0 P:(DE-HGF)0
|a Carr, B.
|b 8
700 1 _ |0 P:(DE-HGF)0
|a Grandis, J.R.
|b 9
700 1 _ |0 P:(DE-HGF)0
|a Bar-Joseph, Z.
|b 10
700 1 _ |0 P:(DE-Juel1)VDB44599
|a Klein-Seetharaman, J.
|b 11
|u FZJ
773 _ _ |0 PERI:(DE-600)2037674-1
|a 10.1002/pmic.200900259
|g Vol. 9, p. 5243 - 5255
|p 5243 - 5255
|q 9<5243 - 5255
|t Proteomics
|v 9
|x 1615-9853
|y 2009
856 7 _ |2 Pubmed Central
|u http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3076061
909 C O |o oai:juser.fz-juelich.de:8400
|p VDB
913 1 _ |0 G:(DE-Juel1)FUEK443
|a DE-HGF
|b Schlüsseltechnologien
|k N03
|l BioSoft
|v Programm Biosoft
|x 0
|z entfällt
914 1 _ |y 2009
915 _ _ |0 StatID:(DE-HGF)0010
|2 StatID
|a JCR/ISI refereed
915 _ _ |0 StatID:(DE-HGF)0100
|2 StatID
|a JCR
915 _ _ |0 StatID:(DE-HGF)0111
|2 StatID
|a WoS
|b Science Citation Index Expanded
915 _ _ |0 StatID:(DE-HGF)0150
|2 StatID
|a DBCoverage
|b Web of Science Core Collection
915 _ _ |0 StatID:(DE-HGF)0199
|2 StatID
|a DBCoverage
|b Thomson Reuters Master Journal List
915 _ _ |0 StatID:(DE-HGF)0300
|2 StatID
|a DBCoverage
|b Medline
920 1 _ |0 I:(DE-Juel1)ISB-2-20090406
|d 31.12.2010
|g ISB
|k ISB-2
|l Molekulare Biophysik
|x 0
970 _ _ |a VDB:(DE-Juel1)117323
980 _ _ |a VDB
980 _ _ |a ConvertedRecord
980 _ _ |a journal
980 _ _ |a I:(DE-Juel1)ICS-6-20110106
980 _ _ |a UNRESTRICTED
981 _ _ |a I:(DE-Juel1)IBI-7-20200312
981 _ _ |a I:(DE-Juel1)ICS-6-20110106
981 _ _ |a I:(DE-Juel1)ISB-2-20090406


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21