Evidence map›Paper›PMID 23918248›Full record

ArticleBioinformatics (Oxford, England)2013

Pclust: protein network visualization highlighting experimental data.

Wenlin Li, Lisa N Kinch, Nick V Grishin

Open access · bronzeAbstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.6field-weighted citation impact, top 30% 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

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Review
  3. Biocuration in the structure-function linkage database: the anatomy of a superfamily.Database : the journal of biological databases and curation · 2017
    Article
  4. Article
  5. Article
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

3 authors at 2 institutions in 1 country.

Wenlin LiDepartments of Biophysics and Biochemistry and Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, TX 75390-9050, USA.
Lisa N Kinch
Nick V Grishin
The University of Texas Southwestern Medical Center · USHoward Hughes Medical Institute · US

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 GM094575
6 · The paper itself

Abstract

summaryOne approach to infer functions of new proteins from their homologs utilizes visualization of an all-against-all pairwise similarity network (A2ApsN) that exploits the speed of BLAST and avoids the complexity of multiple sequence alignment. However, identifying functions of the protein clusters in A2ApsN is never trivial, due to a lack of linking characterized proteins to their relevant information in current software packages. Given the database errors introduced by automatic annotation transfer, functional deduction should be made from proteins with experimental studies, i.e. 'reference proteins'. Here, we present a web server, termed Pclust, which provides a user-friendly interface to visualize the A2ApsN, placing emphasis on such 'reference proteins' and providing access to their full information in source databases, e.g. articles in PubMed. The identification of 'reference proteins' and the ease of cross-database linkage will facilitate understanding the functions of protein clusters in the network, thus promoting interpretation of proteins of interest. AVAILABILITY: The Pclust server is freely available at http://prodata.swmed.edu/pclust

Indexed as

InternetAnimalsDatabases, GeneticMiceProteinsSoftwareProteins

Identifiers

PMID23918248
PMCPMC3789550
OpenAlexW2153117453

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.