Evidence map›Paper›PMID 25938370›Full record

ArticleNature methods2015

Rapid, optimized interactomic screening.

Zhanna Hakhverdyan, Michal Domanski, Loren E Hough, Asha A Oroskar, Anil R Oroskar, Sarah Keegan, David J Dilworth, Kelly R Molloy, Vadim Sherman, John D Aitchison and 5 more

Abstract read
In one paragraph

Article in Nature methods, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

45 citing papers in PubMed.

  1. Article
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  9. Review
  10. Article
  11. Review
  12. MeasuringSTAR protocols · 2021
    Article
  13. Article
  14. Article
  15. Article
  16. NCBP3 positively impacts mRNA biogenesis.Nucleic acids research · 2020
    Article
  17. Article
  18. Review
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Zhanna HakhverdyanLaboratory of Cellular and Structural Biology, The Rockefeller University, New York, New York, USA.
Michal Domanski1] Laboratory of Cellular and Structural Biology, The Rockefeller University, New York, New York, USA. [2] Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark.
Loren E HoughLaboratory of Cellular and Structural Biology, The Rockefeller University, New York, New York, USA.
Asha A OroskarOrochem Technologies Inc., Naperville, Illinois, USA.
Anil R OroskarOrochem Technologies Inc., Naperville, Illinois, USA.
Sarah Keegan1] Center for Health Informatics and Bioinformatics, New York University School of Medicine, New York, New York, USA. [2] Department of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, New York, USA.
David J Dilworth1] Institute for Systems Biology, Seattle, Washington, USA. [2] Seattle Biomedical Research Institute, Seattle, Washington, USA.
Kelly R MolloyLaboratory of Mass Spectrometry and Gaseous Ion Chemistry, The Rockefeller University, New York, New York, USA.
Vadim ShermanHigh Energy Physics Instrument Shop, The Rockefeller University, New York, New York, USA.
John D Aitchison1] Institute for Systems Biology, Seattle, Washington, USA. [2] Seattle Biomedical Research Institute, Seattle, Washington, USA.
David Fenyö1] Center for Health Informatics and Bioinformatics, New York University School of Medicine, New York, New York, USA. [2] Department of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, New York, USA.
Brian T ChaitLaboratory of Mass Spectrometry and Gaseous Ion Chemistry, The Rockefeller University, New York, New York, USA.
Torben Heick JensenDepartment of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark.
Michael P RoutLaboratory of Cellular and Structural Biology, The Rockefeller University, New York, New York, USA.
John LaCavaLaboratory of Cellular and Structural Biology, The Rockefeller University, New York, New York, USA.ORCID 0000000263077713

Funding

Quantitative Systems BiologyP50GM076547 · NIGMS · INSTITUTE FOR SYSTEMS BIOLOGY · PI BALIGA, NITIN S · 2006 to 2016
$30.6M
TR&D Project 4. The Imaging Stage: Multiscale Spatiotemporal Modeling of Macromolecular Systems in Cellular NeighborhoodsP41GM109824 · NIGMS · ROCKEFELLER UNIVERSITY · PI ROUT, MICHAEL P · 2014 to 2023
$18.8M
National Resource for Mass Spectrom of Biological MacromoleculesP41GM103314 · NIGMS · ROCKEFELLER UNIVERSITY · PI CHAIT, BRIAN T · 2012 to 2017
$9.9M
New Tools for Exploring the Dynamic Interactome (Renewal)U54GM103511 · NIGMS · ROCKEFELLER UNIVERSITY · PI ROUT, MICHAEL P · 2012 to 2013
$6.2M
NIGMS NIH HHS P41 GM103314NIGMS NIH HHS P41 GM109824NIGMS NIH HHS P50 GM076547NIGMS NIH HHS U54 GM103511
6 · The paper itself

Abstract

We must reliably map the interactomes of cellular macromolecular complexes in order to fully explore and understand biological systems. However, there are no methods to accurately predict how to capture a given macromolecular complex with its physiological binding partners. Here, we present a screening method that comprehensively explores the parameters affecting the stability of interactions in affinity-captured complexes, enabling the discovery of physiological binding partners in unparalleled detail. We have implemented this screen on several macromolecular complexes from a variety of organisms, revealing novel profiles for even well-studied proteins. Our approach is robust, economical and automatable, providing inroads to the rigorous, systematic dissection of cellular interactomes.

Indexed as

Cell LineEscherichia coliHumansMacromolecular SubstancesProtein Interaction MappingProtein Interaction MapsProteinsProteomicsYeastsMacromolecular SubstancesProteins

Identifiers

PMID25938370
PMCPMC4449307

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

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.