Evidence map›Paper›PMID 24766872›Full record

ArticleBMC bioinformatics2014

ConSole: using modularity of contact maps to locate solenoid domains in protein structures.

Thomas Hrabe, Adam Godzik

Abstract read
In one paragraph

Article in BMC bioinformatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Review
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  14. NAPS: Network Analysis of Protein Structures.Nucleic acids research · 2016
    Article
  15. Article
  16. Tandem Repeats in Proteins: Prediction Algorithms and Biological Role.Frontiers in bioengineering and biotechnology · 2015
    Review
  17. 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

2 authors.

Thomas Hrabe
Adam GodzikProgram in Bioinformatics and Systems Biology, Sanford-Burnham Medical Research Institute, 92037 La Jolla, CA, USA. adam@godziklab.org.

Funding

Development of the flexible comparative modeling toolkitR01GM101457 · NIGMS · SANFORD BURNHAM PREBYS MEDICAL DISCOVERY INSTITUTE · PI GODZIK, ADAM · 2012 to 2015
$1.5M
NIGMS NIH HHS R01 GM101457
6 · The paper itself

Abstract

backgroundPeriodic proteins, characterized by the presence of multiple repeats of short motifs, form an interesting and seldom-studied group. Due to often extreme divergence in sequence, detection and analysis of such motifs is performed more reliably on the structural level. Yet, few algorithms have been developed for the detection and analysis of structures of periodic proteins.

resultsConSole recognizes modularity in protein contact maps, allowing for precise identification of repeats in solenoid protein structures, an important subgroup of periodic proteins. Tests on benchmarks show that ConSole has higher recognition accuracy as compared to Raphael, the only other publicly available solenoid structure detection tool. As a next step of ConSole analysis, we show how detection of solenoid repeats in structures can be used to improve sequence recognition of these motifs and to detect subtle irregularities of repeat lengths in three solenoid protein families.

conclusionsThe ConSole algorithm provides a fast and accurate tool to recognize solenoid protein structures as a whole and to identify individual solenoid repeat units from a structure. ConSole is available as a web-based, interactive server and is available for download at http://console.sanfordburnham.org.

Indexed as

Protein Structure, TertiarySoftwareAlgorithmsLeucine-Rich Repeat ProteinsProtein ConformationProteinsRepetitive Sequences, Amino AcidLeucine-Rich Repeat ProteinsProteins

Identifiers

PMID24766872
PMCPMC4021314

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.