2017Chen Annotation

From 3DEM-Methods
Revision as of 18:57, 7 October 2017 by Coss (talk | contribs) (Created page with "== Citation == Chen, M.; Dai, W.; Sun, S. Y.; Jonasch, D.; He, C. Y.; Schmid, M. F.; Chiu, W. & Ludtke, S. J. Convolutional neural networks for automated annotation of cellul...")
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to navigation Jump to search

Citation

Chen, M.; Dai, W.; Sun, S. Y.; Jonasch, D.; He, C. Y.; Schmid, M. F.; Chiu, W. & Ludtke, S. J. Convolutional neural networks for automated annotation of cellular cryo-electron tomograms. Nature methods, 2017, 14, 983-985

Abstract

Cellular electron cryotomography offers researchers the ability to observe macromolecules frozen in action in situ, but a primary challenge with this technique is identifying molecular components within the crowded cellular environment. We introduce a method that uses neural networks to dramatically reduce the time and human effort required for subcellular annotation and feature extraction. Subsequent subtomogram classification and averaging yield in situ structures of molecular components of interest. The method is available in the EMAN2.2 software package.

Keywords

Links

http://www.nature.com/nmeth/journal/v14/n10/full/nmeth.4405.html

Related software

Related methods

Comments