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High-throughput methods for identification of protein-protein interactions involving short linear motifs

Overview of attention for article published in Cell Communication and Signaling, August 2015
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  • Good Attention Score compared to outputs of the same age (69th percentile)

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Title
High-throughput methods for identification of protein-protein interactions involving short linear motifs
Published in
Cell Communication and Signaling, August 2015
DOI 10.1186/s12964-015-0116-8
Pubmed ID
Authors

Cecilia Blikstad, Ylva Ivarsson

Abstract

Interactions between modular domains and short linear motifs (3-10 amino acids peptide stretches) are crucial for cell signaling. The motifs typically reside in the disordered regions of the proteome and the interactions are often transient, allowing for rapid changes in response to changing stimuli. The properties that make domain-motif interactions suitable for cell signaling also make them difficult to capture experimentally and they are therefore largely underrepresented in the known protein-protein interaction networks. Most of the knowledge on domain-motif interactions is derived from low-throughput studies, although there exist dedicated high-throughput methods for the identification of domain-motif interactions. The methods include arrays of peptides or proteins, display of peptides on phage or yeast, and yeast-two-hybrid experiments. We here provide a survey of scalable methods for domain-motif interaction profiling. These methods have frequently been applied to a limited number of ubiquitous domain families. It is now time to apply them to a broader set of peptide binding proteins, to provide a comprehensive picture of the linear motifs in the human proteome and to link them to their potential binding partners. Despite the plethora of methods, it is still a challenge for most approaches to identify interactions that rely on post-translational modification or context dependent or conditional interactions, suggesting directions for further method development.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 180 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Turkey 1 <1%
Germany 1 <1%
Unknown 177 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 51 28%
Student > Bachelor 25 14%
Researcher 21 12%
Student > Master 19 11%
Professor > Associate Professor 11 6%
Other 25 14%
Unknown 28 16%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 69 38%
Agricultural and Biological Sciences 51 28%
Chemistry 15 8%
Engineering 5 3%
Computer Science 2 1%
Other 9 5%
Unknown 29 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 10 March 2016.
All research outputs
#7,615,670
of 25,959,914 outputs
Outputs from Cell Communication and Signaling
#244
of 1,560 outputs
Outputs of similar age
#82,718
of 280,911 outputs
Outputs of similar age from Cell Communication and Signaling
#1
of 4 outputs
Altmetric has tracked 25,959,914 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 1,560 research outputs from this source. They receive a mean Attention Score of 3.8. This one has done well, scoring higher than 83% 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 280,911 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them