2023Kim Review

From 3DEM-Methods
Revision as of 05:46, 24 August 2023 by WikiSysop (talk | contribs) (Created page with "== Citation == Kim, Hannah Hyun-Sook / Uddin, Mostofa Rafid / Xu, Min / Chang, Yi-Wei. Computational methods toward unbiased pattern mining and structure determination in cry...")
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to navigation Jump to search

Citation

Kim, Hannah Hyun-Sook / Uddin, Mostofa Rafid / Xu, Min / Chang, Yi-Wei. Computational methods toward unbiased pattern mining and structure determination in cryo-electron tomography data. 2023. J. Molecular Biology, p. 168068

Abstract

Cryo-electron tomography can uniquely probe the native cellular environment for macromolecular structures. Tomograms feature complex data with densities of diverse, densely crowded macromolecular complexes, low signal-to-noise, and artifacts such as the missing wedge effect. Post-processing of this data generally involves isolating regions or particles of interest from tomograms, organizing them into related groups, and rendering final structures through subtomogram averaging. Template-matching and reference-based structure determination are popular analysis methods but are vulnerable to biases and can often require significant user input. Most importantly, these approaches cannot identify novel complexes that reside within the imaged cellular environment. To reliably extract and resolve structures of interest, efficient and unbiased approaches are therefore of great value. This review highlights notable computational software and discusses how they contribute to making automated structural pattern discovery a possibility. Perspectives emphasizing the importance of features for user-friendliness and accessibility are also presented.

Keywords

Links

https://www.sciencedirect.com/science/article/pii/S0022283623001274

Related software

Related methods

Comments