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Outlier analyses of the Protein Data Bank archive using a probability-density-ranking approach
Outlier analyses are central to scientific data assessments. Conventional outlier identification methods do not work effectively for Protein Data Bank (PDB) data, which are characterized by heavy skewness and the presence of bounds and/or long tails. We have developed a data-driven nonparametric met...
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| Publicado en: | Sci Data |
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| Main Authors: | , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado: |
Nature Publishing Group
2018
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| Assuntos: | |
| Acceso en liña: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6289109/ https://ncbi.nlm.nih.gov/pubmed/30532050 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/sdata.2018.293 |
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