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  Comparative interactomics analysis of protein family interaction networks using PSIMAP (protein structural interactome map

Park, D., Lee, S., Bolser, D., Schroeder, M., Lappe, M., Oh, D., et al. (2005). Comparative interactomics analysis of protein family interaction networks using PSIMAP (protein structural interactome map. Bioinformatics, 21(15), 3234-3240. doi:10.1093/bioinformatics/bti512.

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Park, Daeui, Autor
Lee, Semin, Autor
Bolser, Dan, Autor
Schroeder, Michael, Autor
Lappe, Michael1, Autor           
Oh, Donghoon, Autor
Bhak, Jong, Autor
Affiliations:
1Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1433554              

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 Zusammenfassung: Motivation: Many genomes have been completely sequenced. However, detecting and analyzing their protein–protein interactions by experimental methods such as co-immunoprecipitation, tandem affinity purification and Y2H is not as fast as genome sequencing. Therefore, a computational prediction method based on the known protein structural interactions will be useful to analyze large-scale protein–protein interaction rules within and among complete genomes. Results: We confirmed that all the predicted protein family interactomes (the full set of protein family interactions within a proteome) of 146 species are scale-free networks, and they share a small core network comprising 36 protein families related to indispensable cellular functions. We found two fundamental differences among prokaryotic and eukaryotic interactomes: (1) eukarya had significantly more hub families than archaea and bacteria and (2) certain special hub families determined the topology of the eukaryotic interactomes. Our comparative analysis suggests that a very small number of expansive protein families led to the evolution of interactomes and seemed to have played a key role in species diversification.

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Sprache(n): eng - English
 Datum: 2005-05-19
 Publikationsstatus: Erschienen
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 Ort, Verlag, Ausgabe: -
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 Identifikatoren: eDoc: 264895
DOI: 10.1093/bioinformatics/bti512
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Titel: Bioinformatics
Genre der Quelle: Zeitschrift
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Seiten: - Band / Heft: 21 (15) Artikelnummer: - Start- / Endseite: 3234 - 3240 Identifikator: ISSN: 1367-4803