Evidence map›Paper›PMID 15740634›Full record

ArticleBMC bioinformatics2005

Computational verification of protein-protein interactions by orthologous co-expression.

Itay Tirosh, Naama Barkai

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.4field-weighted citation impact, top 20% 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

14 citing papers in PubMed, 29 citations in OpenAlex.

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  7. Co-expression among constituents of a motif in the protein-protein interaction network.Journal of bioinformatics and computational biology · 2009
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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 at 1 institution in 1 country.

Itay TiroshDepartment of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel. itay.tirosh@weizmann.ac.il <itay.tirosh@weizmann.ac.il>
Naama Barkai
Weizmann Institute of Science · IL

Funding

PHS HHS A150562
6 · The paper itself

Abstract

backgroundHigh-throughput methods identify an overwhelming number of protein-protein interactions. However, the limited accuracy of these methods results in the false identification of many spurious interactions. Accordingly, the resulting interactions are regarded as hypothetical and computational methods are needed to increase their confidence. Several methods have recently been suggested for this purpose including co-expression as a confidence measure for interacting proteins, but their performance is still quite poor.

resultsWe introduce a novel computational method for verification of protein-protein interactions based on the co-expression of orthologs of interacting partners. The performance of our method is analysed using known S. cerevisiae interactions, and is shown to overcome limitations of previous methods. We present specific examples of known and putative interactions that are detected by our method and not by previous methods, and suggest that they represent transient interactions that might have been conserved and stabilized in other species.

conclusionCo-expression of orthologous protein-pairs can be used to increase the confidence of hypothetical protein-protein interactions in S. cerevisiae as well as in other species. This approach may be especially useful for species with no available expression profiles and for transient interactions.

Indexed as

Gene Expression Regulation, FungalSoftwareAnimalsBinding SitesCloning, MolecularComputational BiologyComputer GraphicsDatabases, GeneticDatabases, ProteinFungal ProteinsGene ExpressionGenes, FungalHumansModels, GeneticModels, StatisticalMolecular ConformationFungal ProteinsProteins

Identifiers

PMID15740634
PMCPMC555590
OpenAlexW2112868113

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.