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  1. Outputs

Random sampling of the Protein Data Bank: RaSPDB

Academic Article
Publication Date:
2021
abstract:
A novel and simple procedure (RaSPDB) for Protein Data Bank mining is described. 10 PDB subsets, each containing 7000 randomly selected protein chains, are built and used to make 10 estimations of the average value of a generic feature F-the length of the protein chain, the amino acid composition, the crystallographic resolution, and the secondary structure composition. These 10 estimations are then used to compute an average estimation of F together with its standard error. It is heuristically verified that the dimension of these 10 subsets-7000 protein chains-is sufficiently small to avoid redundancy within each subset and sufficiently large to guarantee stable estimations amongst different subsets. RaSPDB has two major advantages over classical procedures aimed to build a single, non-redundant PDB subset: a larger fraction of the information stored in the PDB is used and an estimation of the standard error of F is possible.
Iris type:
1.1 Articolo in rivista
Keywords:
Biochemistry, Computational biology and bioinformatics, Molecular biology, Structural biology
List of contributors:
Carugo, Oliviero
Authors of the University:
CARUGO OLIVIERO ITALO
Handle:
https://iris.unipv.it/handle/11571/1468538
Published in:
SCIENTIFIC REPORTS
Journal
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URL

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8683422/
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