↓ Skip to main content

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

Overview of attention for article published in BMC Genomics, February 2015
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 (85th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

twitter
14 X users
facebook
2 Facebook pages
googleplus
1 Google+ user

Citations

dimensions_citation
193 Dimensions

Readers on

mendeley
263 Mendeley
citeulike
1 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
CLIPdb: a CLIP-seq database for protein-RNA interactions
Published in
BMC Genomics, February 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 John 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.

X Demographics

X Demographics

The data shown below were collected from the profiles of 14 X users 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 263 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%
Switzerland 1 <1%
Czechia 1 <1%
Austria 1 <1%
India 1 <1%
Denmark 1 <1%
Unknown 254 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 79 30%
Researcher 44 17%
Student > Master 34 13%
Student > Bachelor 13 5%
Professor 13 5%
Other 34 13%
Unknown 46 17%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 89 34%
Agricultural and Biological Sciences 83 32%
Computer Science 18 7%
Engineering 7 3%
Medicine and Dentistry 6 2%
Other 12 5%
Unknown 48 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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
#3,266,004
of 22,786,691 outputs
Outputs from BMC Genomics
#1,273
of 10,647 outputs
Outputs of similar age
#49,799
of 352,181 outputs
Outputs of similar age from BMC Genomics
#30
of 248 outputs
Altmetric has tracked 22,786,691 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,647 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 88% 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 352,181 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 85% of its contemporaries.
We're also able to compare this research output to 248 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.