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Template-free detection of macromolecular complexes in cryo electron tomograms
Author(s) -
Min Xu,
Martin Beck,
Frank Alber
Publication year - 2011
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btr207
Subject(s) - cryo electron tomography , electron tomography , tomography , resolution (logic) , low resolution , computer science , wedge (geometry) , biological system , inference , algorithm , pattern recognition (psychology) , artificial intelligence , high resolution , physics , biology , electron microscope , optics , geology , remote sensing , scanning transmission electron microscopy
Cryo electron tomography (CryoET) produces 3D density maps of biological specimen in its near native states. Applied to small cells, cryoET produces 3D snapshots of the cellular distributions of large complexes. However, retrieving this information is non-trivial due to the low resolution and low signal-to-noise ratio in tomograms. Current pattern recognition methods identify complexes by matching known structures to the cryo electron tomogram. However, so far only a small fraction of all protein complexes have been structurally resolved. It is, therefore, of great importance to develop template-free methods for the discovery of previously unknown protein complexes in cryo electron tomograms.

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