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CLIPdb: a CLIP-seq database for protein-RNA interactions

Overview of attention for article published in BMC Genomics, January 2015
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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 (84th percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

Mentioned by

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14 tweeters
facebook
2 Facebook pages
googleplus
1 Google+ user

Readers on

mendeley
182 Mendeley
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1 CiteULike
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Title
CLIPdb: a CLIP-seq database for protein-RNA interactions
Published in
BMC Genomics, January 2015
DOI 10.1186/s12864-015-1273-2
Pubmed ID
Authors

Yu-Cheng T Yang, Chao Di, Boqin Hu, Meifeng Zhou, Yifang Liu, Nanxi Song, Yang Li, Jumpei Umetsu, Zhi Lu

Abstract

BackgroundRNA-binding proteins (RBPs) play essential roles in gene expression regulation through their interactions with RNA transcripts, including coding, canonical non-coding and long non-coding RNAs. Large amounts of crosslinking immunoprecipitation (CLIP)-seq data (including HITS-CLIP, PAR-CLIP, and iCLIP) have been recently produced to reveal transcriptome-wide binding sites of RBPs at the single-nucleotide level.DescriptionHere, we constructed a database, CLIPdb, to describe RBP-RNA interactions based on 395 publicly available CLIP-seq data sets for 111 RBPs from four organisms: human, mouse, worm and yeast. We consistently annotated the CLIP-seq data sets and RBPs, and developed a user-friendly interface for rapid navigation of the CLIP-seq data. We applied a unified computational method to identify transcriptome-wide binding sites, making the binding sites directly comparable and the data available for integration across different CLIP-seq studies. The high-resolution binding sites of the RBPs can be visualized on the whole-genome scale using a browser. In addition, users can browse and download the identified binding sites of all profiled RBPs by querying genes of interest, including both protein coding genes and non-coding RNAs.ConclusionManually curated metadata and uniformly identified binding sites of publicly available CLIP-seq data sets will be a foundation for further integrative and comparative analyses. With maintained up-to-date data sets and improved functionality, CLIPdb (http://clipdb.ncrnalab.org) will be a valuable resource for improving the understanding of post-transcriptional regulatory networks.

Twitter Demographics

The data shown below were collected from the profiles of 14 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 182 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 1%
Spain 2 1%
Czechia 1 <1%
India 1 <1%
Austria 1 <1%
Denmark 1 <1%
China 1 <1%
Italy 1 <1%
Switzerland 1 <1%
Other 0 0%
Unknown 171 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 67 37%
Researcher 35 19%
Student > Master 26 14%
Professor 9 5%
Student > Bachelor 9 5%
Other 22 12%
Unknown 14 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 76 42%
Biochemistry, Genetics and Molecular Biology 63 35%
Computer Science 13 7%
Medicine and Dentistry 4 2%
Chemistry 3 2%
Other 7 4%
Unknown 16 9%

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 18 February 2015.
All research outputs
#1,675,505
of 12,378,406 outputs
Outputs from BMC Genomics
#915
of 7,251 outputs
Outputs of similar age
#40,842
of 266,399 outputs
Outputs of similar age from BMC Genomics
#29
of 224 outputs
Altmetric has tracked 12,378,406 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,251 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done well, scoring higher than 87% 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 266,399 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 84% of its contemporaries.
We're also able to compare this research output to 224 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.