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Towards understanding pre-mRNA splicing mechanisms and the role of SR proteins

Overview of attention for article published in Gene, May 2016
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Title
Towards understanding pre-mRNA splicing mechanisms and the role of SR proteins
Published in
Gene, May 2016
DOI 10.1016/j.gene.2016.04.057
Pubmed ID
Authors

Mahbod Sahebi, Mohamed M. Hanafi, Andre J. van Wijnen, Parisa Azizi, Rambod Abiri, Sadegh Ashkani, Sima Taheri

Abstract

Alternative pre-mRNA splicing provides a source of vast protein diversity by removing non-coding sequences (introns) and accurately linking different exonic regions in the correct reading frame. The regulation of alternative splicing is essential for various cellular functions in both pathological and physiological conditions. In eukaryotic cells, this process is commonly used to increase proteomic diversity and to control gene expression either co- or post-transcriptionally. Alternative splicing occurs within a megadalton-sized, multi-component machine consisting of RNA and proteins; during the splicing process, this complex undergoes dynamic changes via RNA-RNA, protein-protein and RNA-protein interactions. Co-transcriptional splicing functionally integrates the transcriptional machinery, thereby enabling the two processes to influence one another, whereas post-transcriptional splicing facilitates the coupling of RNA splicing with post-splicing events. This review addresses the structural aspects of spliceosomes and the mechanistic implications of their stepwise assembly on the regulation of pre-mRNA splicing. Moreover, the role of phosphorylation-based, signal-induced changes in the regulation of the splicing process is demonstrated.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 109 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 <1%
Spain 1 <1%
Italy 1 <1%
Unknown 106 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 29 27%
Researcher 19 17%
Student > Master 19 17%
Student > Bachelor 12 11%
Professor 4 4%
Other 12 11%
Unknown 14 13%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 43 39%
Agricultural and Biological Sciences 32 29%
Medicine and Dentistry 7 6%
Chemistry 3 3%
Computer Science 2 2%
Other 6 6%
Unknown 16 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 May 2016.
All research outputs
#20,653,708
of 25,371,288 outputs
Outputs from Gene
#8,654
of 10,913 outputs
Outputs of similar age
#232,593
of 312,394 outputs
Outputs of similar age from Gene
#63
of 114 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,913 research outputs from this source. They receive a mean Attention Score of 3.8. This one is in the 11th percentile – i.e., 11% of its peers scored the same or lower than it.
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 312,394 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 114 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.