Evidence map›Paper›PMID 19865484›Full record

ArticlePloS one2009

A unique, consistent identifier for alternatively spliced transcript variants.

Alberto Riva, Graziano Pesole

Abstract read
In one paragraph

Article in PloS one, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Alberto RivaDepartment of Molecular Genetics and Microbiology and University of Florida Genetics Institute, University of Florida, Gainesville, Florida, USA. ariva@ufl.edu
Graziano Pesole

Funding

Telethon GGP06158
6 · The paper itself

Abstract

backgroundAs research into alternative splicing reveals the fundamental importance of this phenomenon in the genome expression of higher organisms, there is an increasing need for a standardized, consistent and unique identifier for alternatively spliced isoforms. Such an identifier would be useful to eliminate ambiguities in references to gene isoforms, and would allow for the reliable comparison of isoforms from different sources (e.g., known genes vs. computational predictions). Commonly used identifiers for gene transcripts prove to be unsuitable for this purpose. METHODOLOGY: We propose an algorithm to compute an isoform signature based on the arrangement of exons and introns in a primary transcript. The isoform signature uniquely identifies a transcript structure, and can therefore be used as a key in databases of alternatively spliced isoforms, or to compare alternative splicing predictions produced by different methods. In this paper we present the algorithm to generate isoform signatures, we provide some examples of its application, and we describe a web-based resource to generate isoform signatures and use them in database searches.

conclusionsIsoform signatures are simple, so that they can be easily generated and included in publications and databases, but flexible enough to unambiguously represent all possible isoform structures, including information about coding sequence position and variable transcription start and end sites. We believe that the adoption of isoform signatures can help establish a consistent, unambiguous nomenclature for alternative splicing isoforms. The system described in this paper is freely available at http://genome.ufl.edu/genesig/, and supplementary materials can be found at http://genome.ufl.edu/genesig-files/.

Indexed as

Alternative SplicingTranscription, GeneticAlgorithmsComputational BiologyComputersDatabases, GeneticDatabases, ProteinExonsGenetic VariationGenomicsHumansInternetIntronsProtein IsoformsProtein Isoforms

Identifiers

PMID19865484
PMCPMC2765725

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.