Evidence map›Paper›PMID 28777078›Full record

ReviewActa crystallographica. Section D, Structural biology2017

An overview of comparative modelling and resources dedicated to large-scale modelling of genome sequences.

Su Datt Lam, Sayoni Das, Ian Sillitoe, Christine Orengo

Open access · hybridAbstract readReview
In one paragraph

Review in Acta crystallographica. Section D, Structural biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
3.0field-weighted citation impact, top 8% 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

23 citing papers in PubMed, 55 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Structural and energetic analyses of SARS-CoV-2Computational and structural biotechnology journal · 2022
    Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Structural Biology in the Multi-Omics Era.Journal of chemical information and modeling · 2020
    Article
  17. Article
  18. Homology modeling in the time of collective and artificial intelligence.Computational and structural biotechnology journal · 2020
    Review
  19. Article
  20. 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

4 authors at 2 institutions in 2 countries.

Su Datt LamInstitute of Structural and Molecular Biology, UCL, Darwin Building, Gower Street, London WC1E 6BT, England.
Sayoni DasInstitute of Structural and Molecular Biology, UCL, Darwin Building, Gower Street, London WC1E 6BT, England.
Ian SillitoeInstitute of Structural and Molecular Biology, UCL, Darwin Building, Gower Street, London WC1E 6BT, England.
Christine OrengoInstitute of Structural and Molecular Biology, UCL, Darwin Building, Gower Street, London WC1E 6BT, England.
Institute of Structural and Molecular Biology · GBUniversity College London · GB

Funding

Biotechnology and Biological Sciences Research Council BB/K020013/1Biotechnology and Biological Sciences Research Council BB/N019253/1
6 · The paper itself

Abstract

Computational modelling of proteins has been a major catalyst in structural biology. Bioinformatics groups have exploited the repositories of known structures to predict high-quality structural models with high efficiency at low cost. This article provides an overview of comparative modelling, reviews recent developments and describes resources dedicated to large-scale comparative modelling of genome sequences. The value of subclustering protein domain superfamilies to guide the template-selection process is investigated. Some recent cases in which structural modelling has aided experimental work to determine very large macromolecular complexes are also cited.

Indexed as

GenomeAnimalsDatabases, GeneticGenomicsHumansProtein ConformationProteinsStructural Homology, ProteinProteinscomparative modellingprotein structure predictiontemplate-based modellingtemplate selection

Identifiers

PMID28777078
PMCPMC5571743
OpenAlexW2740279634

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.