Evidence map›Paper›PMID 23356573›Full record

ArticleBMC bioinformatics2013

Seq2Ref: a web server to facilitate functional interpretation.

Wenlin Li, Qian Cong, Lisa N Kinch, Nick V Grishin

Abstract read
In one paragraph

Article in BMC bioinformatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 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

4 authors.

Wenlin LiHoward Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, TX 75390-9050, USA.
Qian Cong
Lisa N Kinch
Nick V Grishin

Funding

Computational methods for structural-functional studies of proteinsR01GM094575 · NIGMS · UT SOUTHWESTERN MEDICAL CENTER · PI GRISHIN, NICK V. · 2010 to 2017
$2.4M
Howard Hughes Medical InstituteNIGMS NIH HHS GM094575NIGMS NIH HHS R01 GM094575
6 · The paper itself

Abstract

backgroundThe size of the protein sequence database has been exponentially increasing due to advances in genome sequencing. However, experimentally characterized proteins only constitute a small portion of the database, such that the majority of sequences have been annotated by computational approaches. Current automatic annotation pipelines inevitably introduce errors, making the annotations unreliable. Instead of such error-prone automatic annotations, functional interpretation should rely on annotations of 'reference proteins' that have been experimentally characterized or manually curated.

resultsThe Seq2Ref server uses BLAST to detect proteins homologous to a query sequence and identifies the reference proteins among them. Seq2Ref then reports publications with experimental characterizations of the identified reference proteins that might be relevant to the query. Furthermore, a plurality-based rating system is developed to evaluate the homologous relationships and rank the reference proteins by their relevance to the query.

conclusionsThe reference proteins detected by our server will lend insight into proteins of unknown function and provide extensive information to develop in-depth understanding of uncharacterized proteins. Seq2Ref is available at: http://prodata.swmed.edu/seq2ref.

Indexed as

Molecular Sequence AnnotationSequence Homology, Amino AcidSoftwareDatabases, ProteinInternetProteinsSequence Analysis, ProteinProteins

Identifiers

PMID23356573
PMCPMC3573977

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.