ArticleNature communications2021
flDPnn: Accurate intrinsic disorder prediction with putative propensities of disorder functions.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 164 papers.
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164 citing papers in PubMed, 311 citations in OpenAlex.
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- A Survey of Predicted Protein-Protein Interactions Involving Disordered Regions in Humans.Journal of molecular biology · 2026Article
- Hybrid deep learning with protein language models and dual-path architecture for predicting IDP functions.Briefings in bioinformatics · 2026Article
- APOL1 plasma membrane pools resist rapid protein degradation.Scientific reports · 2026Article
- Modern resources for intrinsic disorder predictions: protein language models, deep learning, meta-servers, and databases.Cellular and molecular life sciences : CMLS · 2026Review
104 more citing papers are in PubMed but not listed here.
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Authors and funding
7 authors at 2 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Identification of intrinsic disorder in proteins relies in large part on computational predictors, which demands that their accuracy should be high. Since intrinsic disorder carries out a broad range of cellular functions, it is desirable to couple the disorder and disorder function predictions. We report a computational tool, flDPnn, that provides accurate, fast and comprehensive disorder and disorder function predictions from protein sequences. The recent Critical Assessment of protein Intrinsic Disorder prediction (CAID) experiment and results on other test datasets demonstrate that flDPnn offers accurate predictions of disorder, fully disordered proteins and four common disorder functions. These predictions are substantially better than the results of the existing disorder predictors and methods that predict functions of disorder. Ablation tests reveal that the high predictive performance stems from innovative ways used in flDPnn to derive sequence profiles and encode inputs. flDPnn's webserver is available at http://biomine.cs.vcu.edu/servers/flDPnn/.
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