↓ Skip to main content

A General Definition and Nomenclature for Alternative Splicing Events

Overview of attention for article published in PLoS Computational Biology, August 2008
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age and source

Mentioned by

wikipedia
7 Wikipedia pages

Citations

dimensions_citation
214 Dimensions

Readers on

mendeley
391 Mendeley
citeulike
16 CiteULike
connotea
1 Connotea
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
A General Definition and Nomenclature for Alternative Splicing Events
Published in
PLoS Computational Biology, August 2008
DOI 10.1371/journal.pcbi.1000147
Pubmed ID
Authors

Michael Sammeth, Sylvain Foissac, Roderic Guigó

Abstract

Understanding the molecular mechanisms responsible for the regulation of the transcriptome present in eukaryotic cells is one of the most challenging tasks in the postgenomic era. In this regard, alternative splicing (AS) is a key phenomenon contributing to the production of different mature transcripts from the same primary RNA sequence. As a plethora of different transcript forms is available in databases, a first step to uncover the biology that drives AS is to identify the different types of reflected splicing variation. In this work, we present a general definition of the AS event along with a notation system that involves the relative positions of the splice sites. This nomenclature univocally and dynamically assigns a specific "AS code" to every possible pattern of splicing variation. On the basis of this definition and the corresponding codes, we have developed a computational tool (AStalavista) that automatically characterizes the complete landscape of AS events in a given transcript annotation of a genome, thus providing a platform to investigate the transcriptome diversity across genes, chromosomes, and species. Our analysis reveals that a substantial part--in human more than a quarter-of the observed splicing variations are ignored in common classification pipelines. We have used AStalavista to investigate and to compare the AS landscape of different reference annotation sets in human and in other metazoan species and found that proportions of AS events change substantially depending on the annotation protocol, species-specific attributes, and coding constraints acting on the transcripts. The AStalavista system therefore provides a general framework to conduct specific studies investigating the occurrence, impact, and regulation of AS.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 391 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 7 2%
United States 4 1%
Italy 2 <1%
United Kingdom 2 <1%
China 2 <1%
Brazil 2 <1%
Australia 2 <1%
South Africa 2 <1%
Hong Kong 1 <1%
Other 10 3%
Unknown 357 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 118 30%
Researcher 88 23%
Student > Master 44 11%
Student > Bachelor 34 9%
Student > Doctoral Student 18 5%
Other 46 12%
Unknown 43 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 193 49%
Biochemistry, Genetics and Molecular Biology 87 22%
Computer Science 23 6%
Medicine and Dentistry 10 3%
Engineering 7 2%
Other 28 7%
Unknown 43 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 02 December 2019.
All research outputs
#8,544,090
of 25,394,764 outputs
Outputs from PLoS Computational Biology
#5,639
of 8,964 outputs
Outputs of similar age
#35,510
of 99,943 outputs
Outputs of similar age from PLoS Computational Biology
#17
of 41 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,964 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one is in the 33rd percentile – i.e., 33% 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 99,943 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 41 others from the same source and published within six weeks on either side of this one. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.