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Estimation of model accuracy in CASP13
Univ Missouri, MO USA.
Univ Sci, North Korea.
Stockholm Univ, Sweden.
Univ Sci, North Korea.
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2019 (English)In: Proteins: Structure, Function, and Bioinformatics, ISSN 0887-3585, E-ISSN 1097-0134Article in journal (Refereed) Epub ahead of print
Abstract [en]

Methods to reliably estimate the accuracy of 3D models of proteins are both a fundamental part of most protein folding pipelines and important for reliable identification of the best models when multiple pipelines are used. Here, we describe the progress made from CASP12 to CASP13 in the field of estimation of model accuracy (EMA) as seen from the progress of the most successful methods in CASP13. We show small but clear progress, that is, several methods perform better than the best methods from CASP12 when tested on CASP13 EMA targets. Some progress is driven by applying deep learning and residue-residue contacts to model accuracy prediction. We show that the best EMA methods select better models than the best servers in CASP13, but that there exists a great potential to improve this further. Also, according to the evaluation criteria based on local similarities, such as lDDT and CAD, it is now clear that single model accuracy methods perform relatively better than consensus-based methods.

Place, publisher, year, edition, pages
WILEY , 2019.
National Category
Bioinformatics (Computational Biology)
Identifiers
URN: urn:nbn:se:liu:diva-159251DOI: 10.1002/prot.25767ISI: 000476102200001PubMedID: 31265154OAI: oai:DiVA.org:liu-159251DiVA, id: diva2:1340842
Note

Funding Agencies|Research Council of Lithuania [S-MIP-17-60]; National Science Foundation [DBI1759934, IIS1763246]; NIH Office of the Director [R01GM093123]; Vetenskapsradet [2012-5046]

Available from: 2019-08-06 Created: 2019-08-06 Last updated: 2019-08-06

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Wallner, Björn
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BioinformaticsFaculty of Science & Engineering
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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
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