Evidence map›Paper›PMID 25352553›Full record

ArticleNucleic acids research2015

STRING v10: protein-protein interaction networks, integrated over the tree of life.

Damian Szklarczyk, Andrea Franceschini, Stefan Wyder, Kristoffer Forslund, Davide Heller, Jaime Huerta-Cepas, Milan Simonovic, Alexander Roth, Alberto Santos, Kalliopi P Tsafou and 4 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5,917 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5,917citing papers in PubMed, 2 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

5,917 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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5,857 more citing papers are in PubMed but not listed here.

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

14 authors.

Damian SzklarczykInstitute of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland.
Andrea FranceschiniInstitute of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland.
Stefan WyderInstitute of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland.
Kristoffer ForslundEuropean Molecular Biology Laboratory, 69117 Heidelberg, Germany.
Davide HellerInstitute of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland.
Jaime Huerta-CepasEuropean Molecular Biology Laboratory, 69117 Heidelberg, Germany.
Milan SimonovicInstitute of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland.
Alexander RothInstitute of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland.
Alberto SantosNovo Nordisk Foundation Center for Protein Research, University of Copenhagen, 2200 Copenhagen N, Denmark.
Kalliopi P TsafouNovo Nordisk Foundation Center for Protein Research, University of Copenhagen, 2200 Copenhagen N, Denmark.
Michael KuhnBiotechnology Center, Technische Universität Dresden, 01062 Dresden, Germany Max Planck Institute of Molecular Cell Biology and Genetics, 01062 Dresden, Germany.
Peer BorkEuropean Molecular Biology Laboratory, 69117 Heidelberg, Germany bork@embl.de.
Lars J JensenNovo Nordisk Foundation Center for Protein Research, University of Copenhagen, 2200 Copenhagen N, Denmark lars.juhl.jensen@cpr.ku.dk.
Christian von MeringInstitute of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland mering@imls.uzh.ch.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The many functional partnerships and interactions that occur between proteins are at the core of cellular processing and their systematic characterization helps to provide context in molecular systems biology. However, known and predicted interactions are scattered over multiple resources, and the available data exhibit notable differences in terms of quality and completeness. The STRING database (http://string-db.org) aims to provide a critical assessment and integration of protein-protein interactions, including direct (physical) as well as indirect (functional) associations. The new version 10.0 of STRING covers more than 2000 organisms, which has necessitated novel, scalable algorithms for transferring interaction information between organisms. For this purpose, we have introduced hierarchical and self-consistent orthology annotations for all interacting proteins, grouping the proteins into families at various levels of phylogenetic resolution. Further improvements in version 10.0 include a completely redesigned prediction pipeline for inferring protein-protein associations from co-expression data, an API interface for the R computing environment and improved statistical analysis for enrichment tests in user-provided networks.

Indexed as

Databases, ProteinProtein Interaction MappingGene Expression ProfilingInternetProteinsSoftwareProteins

Identifiers

PMID25352553
PMCPMC4383874

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.