Evidence map›Paper›PMID 29931156›Full record

ArticleDatabase : the journal of biological databases and curation2018

RBPMetaDB: a comprehensive annotation of mouse RNA-Seq datasets with perturbations of RNA-binding proteins.

Jin Li, Su-Ping Deng, Jacob Vieira, James Thomas, Valerio Costa, Ching-San Tseng, Franjo Ivankovic, Alfredo Ciccodicola, Peng Yu

Open access · goldAbstract read
In one paragraph

Article in Database : the journal of biological databases and curation, 2018. 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
0.5field-weighted citation impact, top 35% of its field
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, 5 citations in OpenAlex.

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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

9 authors at 6 institutions in 3 countries.

Jin LiDepartment of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843, USA.
Su-Ping DengDepartment of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843, USA.
Jacob VieiraThe Department of Microbiology, University of Massachusetts Amherst, Amherst, MA, USA.
James ThomasDepartment of Molecular Genetics and Microbiology, Center for NeuroGenetics and the Genetics Institute, College of Medicine, University of Florida, Gainesville, FL, USA.
Valerio CostaInstitute of Genetics and Biophysics "Adriano Buzzati-Traverso", Consiglio Nazionale delle Ricerche, Via P. Castellino 111, 80131 Naples, Italy.
Ching-San TsengInstitute of Cellular and Organismic Biology, Academia Sinica, Taipei 11529, Taiwan.
Franjo IvankovicDepartment of Molecular Genetics and Microbiology, Center for NeuroGenetics and the Genetics Institute, College of Medicine, University of Florida, Gainesville, FL, USA.
Alfredo CiccodicolaInstitute of Genetics and Biophysics "Adriano Buzzati-Traverso", Consiglio Nazionale delle Ricerche, Via P. Castellino 111, 80131 Naples, Italy.
Peng YuDepartment of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843, USA.
Texas A&M University · USUniversity of Florida · USInstitute of Cellular and Organismic Biology, Academia Sinica · TWInstitute of Genetics and Biophysics · ITNational Research Council · ITUniversity of Massachusetts Amherst · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

RNA-binding proteins (RBPs) may play a critical role in gene regulation in various diseases or biological processes by controlling post-transcriptional events such as polyadenylation, splicing and mRNA stabilization via binding activities to RNA molecules. Owing to the importance of RBPs in gene regulation, a great number of studies have been conducted, resulting in a large amount of RNA-Seq datasets. However, these datasets usually do not have structured organization of metadata, which limits their potentially wide use. To bridge this gap, the metadata of a comprehensive set of publicly available mouse RNA-Seq datasets with perturbed RBPs were collected and integrated into a database called RBPMetaDB. This database contains 292 mouse RNA-Seq datasets for a comprehensive list of 187 RBPs. These RBPs account for only ∼10% of all known RBPs annotated in Gene Ontology, indicating that most are still unexplored using high-throughput sequencing. This negative information provides a great pool of candidate RBPs for biologists to conduct future experimental studies. In addition, we found that DNA-binding activities are significantly enriched among RBPs in RBPMetaDB, suggesting that prior studies of these DNA- and RNA-binding factors focus more on DNA-binding activities instead of RNA-binding activities. This result reveals the opportunity to efficiently reuse these data for investigation of the roles of their RNA-binding activities. A web application has also been implemented to enable easy access and wide use of RBPMetaDB. It is expected that RBPMetaDB will be a great resource for improving understanding of the biological roles of RBPs.Database URL: http://rbpmetadb.yubiolab.org.

Indexed as

Databases, GeneticMolecular Sequence AnnotationSequence Analysis, RNAAnimalsInternetMiceProtein DomainsPublicationsPubMedRNA-Binding ProteinsStatistics as TopicUser-Computer InterfaceRNA-Binding Proteins

Identifiers

PMID29931156
PMCPMC6009576
OpenAlexW2949725218

What OpenQuestion holds

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LicenceCC BY
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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.