Evidence map›Paper›PMID 24957597›Full record

ArticleNucleic acids research2014

PubServer: literature searches by homology.

Lukasz Jaroszewski, Laszlo Koska, Mayya Sedova, Adam Godzik

Abstract read
In one paragraph

Article in Nucleic acids research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. 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

4 authors.

Lukasz JaroszewskiJoint Center for Structural Genomics (http://www.jcsg.org) Bioinformatics and Systems Biology Program, Sanford Burnham Medical Research Institute, 10901 N. Torrey Pines Road, La Jolla, CA 92037, USA Center for Research in Biological Systems, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0446, USA.
Laszlo KoskaJoint Center for Structural Genomics (http://www.jcsg.org) Bioinformatics and Systems Biology Program, Sanford Burnham Medical Research Institute, 10901 N. Torrey Pines Road, La Jolla, CA 92037, USA.
Mayya SedovaJoint Center for Structural Genomics (http://www.jcsg.org) Bioinformatics and Systems Biology Program, Sanford Burnham Medical Research Institute, 10901 N. Torrey Pines Road, La Jolla, CA 92037, USA.
Adam GodzikJoint Center for Structural Genomics (http://www.jcsg.org) Bioinformatics and Systems Biology Program, Sanford Burnham Medical Research Institute, 10901 N. Torrey Pines Road, La Jolla, CA 92037, USA Center for Research in Biological Systems, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0446, USA adam@godziklab.org.

Funding

Tumor Microenvironment and Cancer ImmunologyP30CA030199 · NCI · SANFORD BURNHAM PREBYS MEDICAL DISCOVERY INSTITUTE · PI Michael Jackson · 1985 to 2026
$107.2M
Structure Determination Core at SSRLU54GM094586 · NIGMS · SCRIPPS RESEARCH INSTITUTE, THE · PI WILSON, IAN A · 2010 to 2014
$40.1M
NCI NIH HHS P30 CA030199NIGMS NIH HHS U54 GM094586
6 · The paper itself

Abstract

PubServer, available at http://pubserver.burnham.org/, is a tool to automatically collect, filter and analyze publications associated with groups of homologous proteins. Protein entries in databases such as Entrez Protein database at NCBI contain information about publications associated with a given protein. The scope of these publications varies a lot: they include studies focused on biochemical functions of individual proteins, but also reports from genome sequencing projects that introduce tens of thousands of proteins. Collecting and analyzing publications related to sets of homologous proteins help in functional annotation of novel protein families and in improving annotations of well-studied protein families or individual genes. However, performing such collection and analysis manually is a tedious and time-consuming process. PubServer automatically collects identifiers of homologous proteins using PSI-Blast, retrieves literature references from corresponding database entries and filters out publications unlikely to contain useful information about individual proteins. It also prepares simple vocabulary statistics from titles, abstracts and MeSH terms to identify the most frequently occurring keywords, which may help to quickly identify common themes in these publications. The filtering criteria applied to collected publications are user-adjustable. The results of the server are presented as an interactive page that allows re-filtering and different presentations of the output.

Indexed as

Sequence Homology, Amino AcidSoftwareData MiningInternetMolecular Sequence AnnotationProteinsProtein Structure, TertiaryPubMedSequence Analysis, ProteinProteins

Identifiers

PMID24957597
PMCPMC4086066

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.