Evidence map›Paper›PMID 23900810›Full record

ArticleProteins2014

Evaluation of predictions in the CASP10 model refinement category.

Timothy Nugent, Domenico Cozzetto, David T Jones

Abstract read
In one paragraph

Article in Proteins, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers.

0numbers the graph read from it
0cells of the map it votes in
63citing 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

63 citing papers in PubMed.

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3 more citing papers are in PubMed but not listed here.

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.

Timothy NugentDepartment of Computer Science Bioinformatics Group, University College London, London, WC1E 6BT, United Kingdom.
Domenico Cozzetto
David T Jones

Funding

Biotechnology and Biological Sciences Research Council BB/J002925/1Medical Research Council G0902087
6 · The paper itself

Abstract

Here we report on the assessment results of the third experiment to evaluate the state of the art in protein model refinement, where participants were invited to improve the accuracy of initial protein models for 27 targets. Using an array of complementary evaluation measures, we find that five groups performed better than the naïve (null) method-a marked improvement over CASP9, although only three were significantly better. The leading groups also demonstrated the ability to consistently improve both backbone and side chain positioning, while other groups reliably enhanced other aspects of protein physicality. The top-ranked group succeeded in improving the backbone conformation in almost 90% of targets, suggesting a strategy that for the first time in CASP refinement is successful in a clear majority of cases. A number of issues remain unsolved: the majority of groups still fail to improve the quality of the starting models; even successful groups are only able to make modest improvements; and no prediction is more similar to the native structure than to the starting model. Successful refinement attempts also often go unrecognized, as suggested by the relatively larger improvements when predictions not submitted as model 1 are also considered.

Indexed as

Computational BiologyModels, MolecularProtein ConformationAlgorithmsModels, StatisticalProteinsSequence AlignmentProteinsCASPmodel quality evaluationprotein model refinementprotein structure predictiontemplate-based modeling

Identifiers

PMID23900810
PMCPMC4282348

What OpenQuestion holds

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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.