Evidence map›Paper›PMID 27489291›Full record

ArticleMolecular & cellular proteomics : MCP2016

Cell-free Determination of Binary Complexes That Comprise Extended Protein-Protein Interaction Networks of Yersinia pestis.

Sarah L Keasey, Mohan Natesan, Christine Pugh, Teddy Kamata, Stefan Wuchty, Robert G Ulrich

Open access · hybridAbstract read
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 94% of its field
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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

6 authors at 3 institutions in 1 country.

Sarah L KeaseyFrom the ‡Molecular and Translational Sciences Division, U.S. Army Medical Research Institute of Infectious Diseases, Frederick, Maryland 21702; §Biological Sciences Department, University of Maryland Baltimore County, Baltimore, Maryland 21250.
Mohan NatesanFrom the ‡Molecular and Translational Sciences Division, U.S. Army Medical Research Institute of Infectious Diseases, Frederick, Maryland 21702.
Christine PughFrom the ‡Molecular and Translational Sciences Division, U.S. Army Medical Research Institute of Infectious Diseases, Frederick, Maryland 21702.
Teddy KamataFrom the ‡Molecular and Translational Sciences Division, U.S. Army Medical Research Institute of Infectious Diseases, Frederick, Maryland 21702.
Stefan Wuchty¶National Center for Biotechnology Information, National Institutes of Health, Bethesda, Maryland 20892.
Robert G UlrichFrom the ‡Molecular and Translational Sciences Division, U.S. Army Medical Research Institute of Infectious Diseases, Frederick, Maryland 21702; rulrich@bhsai.org.
United States Army Medical Research Institute of Infectious Diseases · USNational Institutes of Health · USUniversity of Maryland, Baltimore County · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Binary protein interactions form the basic building blocks of molecular networks and dynamic assemblies that control all cellular functions of bacteria. Although these protein interactions are a potential source of targets for the development of new antibiotics, few high-confidence data sets are available for the large proteomes of most pathogenic bacteria. We used a library of recombinant proteins from the plague bacterium Yersinia pestis to probe planar microarrays of immobilized proteins that represented ∼85% (3552 proteins) of the bacterial proteome, resulting in >77,000 experimentally determined binary interactions. Moderate (K

Indexed as

Bacterial ProteinsCell-Free SystemCluster AnalysisComputational BiologyProtein Array AnalysisProtein Interaction MapsProteomicsSurface Plasmon ResonanceYersinia pestisBacterial Proteins

Identifiers

PMID27489291
PMCPMC5054345
OpenAlexW2477341565

What OpenQuestion holds

Textmetadata
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.