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D2P2: database of disordered protein predictions

2012· article· en· 730 citations· W2170563234 sur OpenAlex· 10.1093/nar/gks1226

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Résumé

We present the Database of Disordered Protein Prediction (D(2)P(2)), available at http://d2p2.pro (including website source code). A battery of disorder predictors and their variants, VL-XT, VSL2b, PrDOS, PV2, Espritz and IUPred, were run on all protein sequences from 1765 complete proteomes (to be updated as more genomes are completed). Integrated with these results are all of the predicted (mostly structured) SCOP domains using the SUPERFAMILY predictor. These disorder/structure annotations together enable comparison of the disorder predictors with each other and examination of the overlap between disordered predictions and SCOP domains on a large scale. D(2)P(2) will increase our understanding of the interplay between disorder and structure, the genomic distribution of disorder, and its evolutionary history. The parsed data are made available in a unified format for download as flat files or SQL tables either by genome, by predictor, or for the complete set. An interactive website provides a graphical view of each protein annotated with the SCOP domains and disordered regions from all predictors overlaid (or shown as a consensus). There are statistics and tools for browsing and comparing genomes and their disorder within the context of their position on the tree of life.

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La notice

Revue
Nucleic Acids Research
Thématique
Protein Structure and Dynamics
Domaine
Biochemistry, Genetics and Molecular Biology
Établissements canadiens
Organismes subventionnaires
Russian Academy of SciencesBiotechnology and Biological Sciences Research CouncilNatural Sciences and Engineering Research Council of CanadaEngineering and Physical Sciences Research CouncilDirectorate for Biological SciencesUniversity of AlbertaNational Science Foundation
Mots-clés
BiologyContext (archaeology)GenomeProteomeDownloadParsingSet (abstract data type)Source codeComputational biologyTree (set theory)Computer scienceBioinformaticsGeneticsArtificial intelligenceWorld Wide WebGeneProgramming language
Résumé présent dans OpenAlex
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