Alisia Fadini
@alisiafadini.bsky.social did:plc:njgjuave7loexmk6jceth66n
Researcher. Learning biomolecular function and dynamics beyond the single-structure frontier @Columbia University
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Alisia Fadini (@alisiafadini.bsky.social) es un usuario de Bluesky que se unió el 12 diciembre 2024. Tiene 424 seguidores, sigue a 247 cuentas y ha publicado 51 posts.
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Ver post5/5 So rather than asking whether a dataset “contains an ensemble,” we suggest thinking in terms of a new research frontier: ** ensemble resolution ** Specifically, what differences between distributions can your data distinguish? What do you think? Let us know!
Ver post4/5 Then comes processing. Cryo-EM preserves molecule-to-molecule variation, but filtering, alignment, classification, and reconstruction can remove or compress that information. Crucially, a reconstruction can gain spatial resolution while losing ensemble information.
Ver post3/5 Single-particle measurements preserve variation more directly. But neither case gives you the ensemble for free. Averaged data constrain only certain features of the distribution. In single-particle, noise, nuisance variables, and finite sampling interfere.
Ver post2/5 Different experiments encode the distributions in very different ways. An averaged measurement like X-ray diffraction can still contain a distribution: averaging observables is not the same as averaging structures.
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