Deep Spectral Clustering (DSC) Algorithm: A convolutional autoencoder (CAE) is trained on input image stack (<i>S</i>) to extract latent feature vectors (<i>LFV</i>).

Deep Spectral Clustering (DSC) Algorithm: A convolutional autoencoder (CAE) is trained on input image stack (<i>S</i>) to extract latent feature vectors (<i>LFV</i>).

<p><i>LFV</i> pairs are compared by a given distance metric (DM) to construct an affinity matrix (<i>A</i>). Spectral clustering (SC) is applied to <i>A</i>, returning <i>n</i> cluster labels for the input stack. Images are grouped by label into...

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Bibliographic Details
Main Author:	Creighton M. Lisowski (22756444) (author)
Other Authors:	Gavin M. King (1316184) (author), Ioan Kosztin (3917603) (author)
Published:	2025
Subjects:	Biophysics Biochemistry Medicine Biotechnology Developmental Biology Infectious Diseases Computational Biology Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified Physical Sciences not elsewhere classified reconstructing peak positions molecular dynamics simulations handle biological macromolecules demonstrate improved resolution individual protein conformations general lafm algorithm afm image stacks protein conformation multiple conformations work represents step towards simultaneously registers secyeg translocon recording frequency native conditions less effective flexible proteins create images clusters images automated registration
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