Enhanced intensity-based clustering of isomorphous multi-crystal data sets in the presence of subtle variations

Thompson, A.J.; Beilsten-Edmands, J.; Tam, C.; Sanchez-Weatherby, J.; Sandy, J.; Mikolajek, H.; Axford, D.; Jaho, S.; Hough, M.A.; Winter, G.

doi:10.1107/S2059798325004589

Acta Crystallographica Section D
Acta Crystallographica
Section D STRUCTURAL BIOLOGY

IUCr IT WDC

home archive editors for authors for readers submit subscribe open access

view article

Figure 2
Graphical representation of the spatial density-based clustering results produced by OPTICS (Ankerst et al., 1999

). Data points are represented as black dots, with circles of different colours (A, B, C and D) representing clusters. By not including a global density requirement, clusters of different spatial densities can be automatically separated (A, B, C and D), whereas a global density requirement would either join C and D together or omit A and B entirely. The same concept applies in higher dimensions.