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![[Figure 3]](rr5246fig3mag.jpg)
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Figure 3
Schematic workflow of the automatic detection algorithm. The process begins with a low-angle data subset A. Subsequently, crystallographic statistics and clustering bootstrapping are performed independently. The overlap between each subcluster Ci,j and the set O derived from crystallographic statistics is then assessed. This results in the concatenated multiset ![[{\hat {\bi C}}]](teximages/rr5246fi10.svg){kind=small} , where elements can be recurrent with a certain multiplicity. If an unique element has sufficient multiplicity, it will be included in the output set N and categorized as a NEMO. The detection performance is influenced by the hyperparameters t, l and m. Here, an element p is equivalent to indexed 2D coordinates with (x, y) as positional properties in a Euclidean plane. |
![[Figure 3]](rr5246fig3.jpg)
 | STRUCTURAL BIOLOGY |
ISSN: 2059-7983
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