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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Detalles Bibliográficos
Autores principales: Shao, Chenghua, Liu, Zonghong, Yang, Huanwang, Wang, Sijian, Burley, Stephen K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2018
Materias:
Analysis
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6289109/
https://www.ncbi.nlm.nih.gov/pubmed/30532050
http://dx.doi.org/10.1038/sdata.2018.293

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6289109/
https://www.ncbi.nlm.nih.gov/pubmed/30532050
http://dx.doi.org/10.1038/sdata.2018.293

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