ArticleProteins2014
Assessment of protein disorder region predictions in CASP10.
Article in Proteins, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 83 papers.
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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
83 citing papers in PubMed, 164 citations in OpenAlex.
- Modern resources for intrinsic disorder predictions: protein language models, deep learning, meta-servers, and databases.Cellular and molecular life sciences : CMLS · 2026Review
- Predicting Pose Distribution of Protein Domains Connected by Flexible Linkers Is an Unsolved Problem.Proteins · 2026Article
- Decoding intrinsically disordered regions in biomolecular condensates.Fundamental research · 2026Review
- Evaluation of predictions of disordered binding regions in the CAID2 experiment.Computational and structural biotechnology journal · 2025Review
- Prediction of Disordered Linear Interacting Peptides with CLIP.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Accurate and Fast Prediction of Intrinsic Disorder Using flDPnn.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Assessment of Disordered Linker Predictions in the CAID2 Experiment.Biomolecules · 2024Article
- Tutorial: a guide for the selection of fast and accurate computational tools for the prediction of intrinsic disorder in proteins.Nature protocols · 2023Review
- DEPICTER2: a comprehensive webserver for intrinsic disorder and disorder function prediction.Nucleic acids research · 2023Article
- Development of a candidate multi-epitope vaccine againstSaudi medical journal · 2023Article
- Computational Prediction of Protein Intrinsically Disordered Region Related Interactions and Functions.Genes · 2023Review
- Computational prediction of disordered binding regions.Computational and structural biotechnology journal · 2023Review
- Computational Methods to Predict Intrinsically Disordered Regions and Functional Regions in Them.Methods in molecular biology (Clifton, N.J.) · 2023Review
- Compositional Bias of Intrinsically Disordered Proteins and Regions and Their Predictions.Biomolecules · 2022Article
- SETH predicts nuances of residue disorder from protein embeddings.Frontiers in bioinformatics · 2022Article
- Complementarity of the residue-level protein function and structure predictions in human proteins.Computational and structural biotechnology journal · 2022Article
- Predicting Protein Conformational Disorder and Disordered Binding Sites.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Deep learning in prediction of intrinsic disorder in proteins.Computational and structural biotechnology journal · 2022Review
- Metapredict: a fast, accurate, and easy-to-use predictor of consensus disorder and structure.Biophysical journal · 2021Article
- flDPnn: Accurate intrinsic disorder prediction with putative propensities of disorder functions.Nature communications · 2021Article
23 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
Abstract
The article presents the assessment of disorder region predictions submitted to CASP10. The evaluation is based on the three measures tested in previous CASPs: (i) balanced accuracy, (ii) the Matthews correlation coefficient for the binary predictions, and (iii) the area under the curve in the receiver operating characteristic (ROC) analysis of predictions using probability annotation. We also performed new analyses such as comparison of the submitted predictions with those obtained with a Naïve disorder prediction method and with predictions from the disorder prediction databases D2P2 and MobiDB. On average, the methods participating in CASP10 demonstrated slightly better performance than those in CASP9.
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Registered trials
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.