ArticleProteins2016
Analysis of free modeling predictions by RBO aleph in CASP11.
Article in Proteins, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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.
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Who cites it
3 citing papers in PubMed.
- DNCON2: improved protein contact prediction using two-level deep convolutional neural networks.Bioinformatics (Oxford, England) · 2018Article
- CONFOLD2: improved contact-driven ab initio protein structure modeling.BMC bioinformatics · 2018Article
- UniCon3D: de novo protein structure prediction using united-residue conformational search via stepwise, probabilistic sampling.Bioinformatics (Oxford, England) · 2016Article
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Authors and funding
5 authors.
Funding
Abstract
The CASP experiment is a biannual benchmark for assessing protein structure prediction methods. In CASP11, RBO Aleph ranked as one of the top-performing automated servers in the free modeling category. This category consists of targets for which structural templates are not easily retrievable. We analyze the performance of RBO Aleph and show that its success in CASP was a result of its ab initio structure prediction protocol. A detailed analysis of this protocol demonstrates that two components unique to our method greatly contributed to prediction quality: residue-residue contact prediction by EPC-map and contact-guided conformational space search by model-based search (MBS). Interestingly, our analysis also points to a possible fundamental problem in evaluating the performance of protein structure prediction methods: Improvements in components of the method do not necessarily lead to improvements of the entire method. This points to the fact that these components interact in ways that are poorly understood. This problem, if indeed true, represents a significant obstacle to community-wide progress. Proteins 2016; 84(Suppl 1):87-104. © 2015 Wiley Periodicals, Inc.
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