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Measuring the similarity of SMLM-derived point-clouds

Baragilly, M.; Nieves, D.; Williamson, D.; Peters, R.; Owen, D.

2022-09-14 biophysics
10.1101/2022.09.12.507560 bioRxiv
Show abstract

Single-molecule localisation microscopy produces data in the form of point-clouds. Here, we present a tool for assessing the similarity of two such point-clouds, which, unlike measures such as co-localisation, is insensitive to differences that are not preserved between data sets. The presented method can determine whether two point-clouds were generated from the same conditions and can identify from which of two experimental conditions an unseen point-cloud was likely derived.

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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.