Evidence map›Paper›PMID 21051348›Full record

ArticleNucleic acids research2011

ASPicDB: a database of annotated transcript and protein variants generated by alternative splicing.

Pier L Martelli, Mattia D'Antonio, Paola Bonizzoni, Tiziana Castrignanò, Anna M D'Erchia, Paolo D'Onorio De Meo, Piero Fariselli, Michele Finelli, Flavio Licciulli, Marina Mangiulli and 10 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

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  17. DBATE: database of alternative transcripts expression.Database : the journal of biological databases and curation · 2013
    Article
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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

20 authors.

Pier L MartelliBiocomputing Group, University of Bologna, Bologna 40126, Italy.
Mattia D'Antonio
Paola Bonizzoni
Tiziana Castrignanò
Anna M D'Erchia
Paolo D'Onorio De Meo
Piero Fariselli
Michele Finelli
Flavio Licciulli
Marina Mangiulli
Flavio Mignone
Giulio Pavesi
Ernesto Picardi
Raffaella Rizzi
Ivan Rossi
Alessio Valletti
Andrea Zauli
Federico Zambelli
Rita Casadio
Graziano Pesole

Funding

Telethon GGP06158
6 · The paper itself

Abstract

Alternative splicing is emerging as a major mechanism for the expansion of the transcriptome and proteome diversity, particularly in human and other vertebrates. However, the proportion of alternative transcripts and proteins actually endowed with functional activity is currently highly debated. We present here a new release of ASPicDB which now provides a unique annotation resource of human protein variants generated by alternative splicing. A total of 256,939 protein variants from 17,191 multi-exon genes have been extensively annotated through state of the art machine learning tools providing information of the protein type (globular and transmembrane), localization, presence of PFAM domains, signal peptides, GPI-anchor propeptides, transmembrane and coiled-coil segments. Furthermore, full-length variants can be now specifically selected based on the annotation of CAGE-tags and polyA signal and/or polyA sites, marking transcription initiation and termination sites, respectively. The retrieval can be carried out at gene, transcript, exon, protein or splice site level allowing the selection of data sets fulfilling one or more features settled by the user. The retrieval interface also enables the selection of protein variants showing specific differences in the annotated features. ASPicDB is available at http://www.caspur.it/ASPicDB/.

Indexed as

Alternative SplicingDatabases, GeneticExonsGenetic VariationHumansProtein IsoformsProteinsRNA, MessengerSequence Analysis, ProteinUser-Computer InterfaceProtein IsoformsProteinsRNA, Messenger

Identifiers

PMID21051348
PMCPMC3013677

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Registered trials

None linked

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.