Evidence map›Paper›PMID 19108706›Full record

ArticleBMC genomics2008

An evolutionary and structural characterization of mammalian protein complex organization.

Philip Wong, Sonja Althammer, Andrea Hildebrand, Andreas Kirschner, Philipp Pagel, Bernd Geissler, Pawel Smialowski, Florian Blöchl, Matthias Oesterheld, Thorsten Schmidt and 4 more

Abstract read
In one paragraph

Article in BMC genomics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Article
  2. Defining Pharmacological Targets by Analysis of Virus-Host Protein Interactions.Advances in protein chemistry and structural biology · 2018
    Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Hypergraphs and cellular networks.PLoS computational biology · 2009
    Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

14 authors.

Philip WongHelmholtz Center Munich-German Research Center for Environmental Health (GmbH), Institute of Bioinformatics and Systems Biology, Ingolstädter Landstrasse 1, Neuherberg, Germany. philip.wong@helmholtz-muenchen.de
Sonja Althammer
Andrea Hildebrand
Andreas Kirschner
Philipp Pagel
Bernd Geissler
Pawel Smialowski
Florian Blöchl
Matthias Oesterheld
Thorsten Schmidt
Normann Strack
Fabian J Theis
Andreas Ruepp
Dmitrij Frishman

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe have recently released a comprehensive, manually curated database of mammalian protein complexes called CORUM. Combining CORUM with other resources, we assembled a dataset of over 2700 mammalian complexes. The availability of a rich information resource allows us to search for organizational properties concerning these complexes.

resultsAs the complexity of a protein complex in terms of the number of unique subunits increases, we observed that the number of such complexes and the mean non-synonymous to synonymous substitution ratio of associated genes tend to decrease. Similarly, as the number of different complexes a given protein participates in increases, the number of such proteins and the substitution ratio of the associated gene also tends to decrease. These observations provide evidence relating natural selection and the organization of mammalian complexes. We also observed greater homogeneity in terms of predicted protein isoelectric points, secondary structure and substitution ratio in annotated versus randomly generated complexes. A large proportion of the protein content and interactions in the complexes could be predicted from known binary protein-protein and domain-domain interactions. In particular, we found that large proteins interact preferentially with much smaller proteins.

conclusionWe observed similar trends in yeast and other data. Our results support the existence of conserved relations associated with the mammalian protein complexes.

Indexed as

Databases, ProteinEvolution, MolecularProtein Interaction MappingAnimalsComputational BiologyLinear ModelsMammalsModels, MolecularMultiprotein ComplexesProtein Structure, SecondaryProteomicsSequence Analysis, ProteinMultiprotein Complexes

Identifiers

PMID19108706
PMCPMC2645396

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.