↓ Skip to main content

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

Overview of attention for article published in Nucleic Acids Research, October 2014
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • Good Attention Score compared to outputs of the same age and source (79th percentile)

Mentioned by

twitter
13 tweeters
facebook
1 Facebook page
wikipedia
7 Wikipedia pages

Citations

dimensions_citation
8074 Dimensions

Readers on

mendeley
3975 Mendeley
citeulike
9 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
STRING v10: protein–protein interaction networks, integrated over the tree of life
Published in
Nucleic Acids Research, October 2014
DOI 10.1093/nar/gku1003
Pubmed ID
Authors

Damian Szklarczyk, Andrea Franceschini, Stefan Wyder, Kristoffer Forslund, Davide Heller, Jaime Huerta-Cepas, Milan Simonovic, Alexander Roth, Alberto Santos, Kalliopi P. Tsafou, Michael Kuhn, Peer Bork, Lars J. Jensen, Christian von Mering

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.

Twitter Demographics

Twitter Demographics

The data shown below were collected from the profiles of 13 tweeters who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3,975 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 20 <1%
United States 13 <1%
Germany 10 <1%
France 6 <1%
Brazil 4 <1%
South Africa 4 <1%
Luxembourg 3 <1%
Turkey 3 <1%
Spain 3 <1%
Other 33 <1%
Unknown 3876 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 945 24%
Researcher 584 15%
Student > Master 554 14%
Student > Bachelor 429 11%
Student > Doctoral Student 240 6%
Other 552 14%
Unknown 671 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 1089 27%
Biochemistry, Genetics and Molecular Biology 1070 27%
Medicine and Dentistry 222 6%
Computer Science 167 4%
Chemistry 88 2%
Other 509 13%
Unknown 830 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 October 2022.
All research outputs
#3,374,369
of 23,344,526 outputs
Outputs from Nucleic Acids Research
#4,678
of 26,564 outputs
Outputs of similar age
#40,723
of 261,845 outputs
Outputs of similar age from Nucleic Acids Research
#87
of 419 outputs
Altmetric has tracked 23,344,526 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 26,564 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.7. This one has done well, scoring higher than 77% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 261,845 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 419 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.