ArticleProteins2019
CASP13 target classification into tertiary structure prediction categories.
Article in Proteins, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Beyond Single Chains: Benchmarking Macromolecular Complex Prediction Methods With the Continuous Automated Model EvaluatiOn (CAMEO).Proteins · 2026Article
- Template-based RNA structure prediction advanced through a blind code competition.bioRxiv : the preprint server for biology · 2025Article
- Dissecting AlphaFold2's capabilities with limited sequence information.Bioinformatics advances · 2025Article
- To split or not to split: CASP15 targets and their processing into tertiary structure evaluation units.Proteins · 2023Article
- Easy Not Easy: Comparative Modeling with High-Sequence Identity Templates.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Progressive assembly of multi-domain protein structures from cryo-EM density maps.Nature computational science · 2022Article
- A-Prot: protein structure modeling using MSA transformer.BMC bioinformatics · 2022Article
- Ultrafast end-to-end protein structure prediction enables high-throughput exploration of uncharacterized proteins.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Continuous Automated Model EvaluatiOn (CAMEO)-Perspectives on the future of fully automated evaluation of structure prediction methods.Proteins · 2021Article
- Assessment of domain interactions in the fourteenth round of the Critical Assessment of Structure Prediction (CASP14).Proteins · 2021Article
- Target classification in the 14th round of the critical assessment of protein structure prediction (CASP14).Proteins · 2021Article
- Assessment of protein model structure accuracy estimation in CASP14: Old and new challenges.Proteins · 2021Article
- Deep template-based protein structure prediction.PLoS computational biology · 2021Article
- Progressive and accurate assembly of multi-domain protein structures from cryo-EM density maps.bioRxiv : the preprint server for biology · 2020Article
- AWSEM-Suite: a protein structure prediction server based on template-guided, coevolutionary-enhanced optimized folding landscapes.Nucleic acids research · 2020Article
- Improved Consensus-Fragment Selection in Template-Assisted Prediction of Protein Structures with the UNRES Force Field in CASP13.Journal of chemical information and modeling · 2020Article
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- Assessment of protein model structure accuracy estimation in CASP13: Challenges in the era of deep learning.Proteins · 2019Article
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4 authors.
Funding
Abstract
Protein target structures for the Critical Assessment of Structure Prediction round 13 (CASP13) were split into evaluation units (EUs) based on their structural domains, the domain organization of available templates, and the performance of servers on whole targets compared to split target domains. Eighty targets were split into 112 EUs. The EUs were classified into categories suitable for assessment of high accuracy modeling (or template-based modeling [TBM]) and topology (or free modeling [FM]) based on target difficulty. Assignment into assessment categories considered the following criteria: (a) the evolutionary relationship of target domains to existing fold space as defined by the Evolutionary Classification of Protein Domains (ECOD) database; (b) the clustering of target domains using eight objective sequence, structure, and performance measures; and (c) the placement of target domains in a scatter plot of target difficulty against server performance used in the previous CASP. Generally, target domains with good server predictions had close template homologs and were classified as TBM. Alternately, targets with poor server predictions represent a mixture of fast evolving homologs, structure analogs, and new folds, and were classified as FM or FM/TBM overlap.
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