Evidence map›Paper›PMID 19632888›Full record

ReviewCurrent opinion in microbiology2009

Connecting viral with cellular interactomes.

S M Bailer, J Haas

Abstract readReview
In one paragraph

Review in Current opinion in microbiology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 1 pooled it
–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

29 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

2 authors.

S M BailerMax-von-Pettenkofer Institut, Ludwig-Maximilians-Universität München, Muenchen, Germany. Bailer@mvp.uni-muenchen.de
J Haas

Funding

Medical Research Council G050145Medical Research Council G0501453
6 · The paper itself

Abstract

Genome-scale screens for intraviral and virus-host protein interactions and the analysis of literature-curated datasets are able to provide a novel, comprehensive perspective of viruses, and virus-infected cells. Until now, large-scale interaction screens were predominantly performed with the yeast-two-hybrid (Y2H) system; however, alternative high-throughput technologies detecting binary protein interactions or protein complexes have been developed. Although many of the previous studies suffer from a rather poor validation of the results and few biological implications, these technologies potentially lead to a plethora of novel hypotheses. Here, we will give an overview of current approaches and their technical limitations, present recent examples and novel developments.

Indexed as

Host-Pathogen InteractionsCellsGene Expression ProfilingGenomicsProtein Interaction MappingProteomicsSystems BiologyTwo-Hybrid System TechniquesViruses

Identifiers

PMID19632888
PMCPMC7108267

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.