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Discovery of Protein–lncRNA Interactions by Integrating Large-Scale CLIP-Seq and RNA-Seq Datasets

Overview of attention for article published in Frontiers in Bioengineering and Biotechnology, 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 (90th percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Mentioned by

blogs
1 blog
twitter
13 X users
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1 Facebook page

Citations

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74 Dimensions

Readers on

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134 Mendeley
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Title
Discovery of Protein–lncRNA Interactions by Integrating Large-Scale CLIP-Seq and RNA-Seq Datasets
Published in
Frontiers in Bioengineering and Biotechnology, January 2015
DOI 10.3389/fbioe.2014.00088
Pubmed ID
Authors

Jun-Hao Li, Shun Liu, Ling-Ling Zheng, Jie Wu, Wen-Ju Sun, Ze-Lin Wang, Hui Zhou, Liang-Hu Qu, Jian-Hua Yang

Abstract

Long non-coding RNAs (lncRNAs) are emerging as important regulatory molecules in developmental, physiological, and pathological processes. However, the precise mechanism and functions of most of lncRNAs remain largely unknown. Recent advances in high-throughput sequencing of immunoprecipitated RNAs after cross-linking (CLIP-Seq) provide powerful ways to identify biologically relevant protein-lncRNA interactions. In this study, by analyzing millions of RNA-binding protein (RBP) binding sites from 117 CLIP-Seq datasets generated by 50 independent studies, we identified 22,735 RBP-lncRNA regulatory relationships. We found that one single lncRNA will generally be bound and regulated by one or multiple RBPs, the combination of which may coordinately regulate gene expression. We also revealed the expression correlation of these interaction networks by mining expression profiles of over 6000 normal and tumor samples from 14 cancer types. Our combined analysis of CLIP-Seq data and genome-wide association studies data discovered hundreds of disease-related single nucleotide polymorphisms resided in the RBP binding sites of lncRNAs. Finally, we developed interactive web implementations to provide visualization, analysis, and downloading of the aforementioned large-scale datasets. Our study represented an important step in identification and analysis of RBP-lncRNA interactions and showed that these interactions may play crucial roles in cancer and genetic diseases.

X Demographics

X Demographics

The data shown below were collected from the profiles of 13 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 134 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 1%
Chile 1 <1%
United Kingdom 1 <1%
South Africa 1 <1%
Spain 1 <1%
Denmark 1 <1%
Unknown 127 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 41 31%
Researcher 30 22%
Student > Master 16 12%
Student > Doctoral Student 7 5%
Student > Bachelor 6 4%
Other 19 14%
Unknown 15 11%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 52 39%
Agricultural and Biological Sciences 45 34%
Medicine and Dentistry 6 4%
Computer Science 5 4%
Neuroscience 3 2%
Other 6 4%
Unknown 17 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 08 August 2015.
All research outputs
#2,365,494
of 23,495,502 outputs
Outputs from Frontiers in Bioengineering and Biotechnology
#285
of 7,096 outputs
Outputs of similar age
#34,574
of 357,243 outputs
Outputs of similar age from Frontiers in Bioengineering and Biotechnology
#3
of 45 outputs
Altmetric has tracked 23,495,502 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,096 research outputs from this source. They receive a mean Attention Score of 3.5. This one has done particularly well, scoring higher than 95% 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 357,243 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 45 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.