PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Adaptive nonparametric detection in cryo-electron microscopy
Mikhail Langovoy, Michael Habeck and Bernhard Schölkopf
In: 58th World Statistics Congress of the International Statistical Institute (ISI 2011)(2011).


Introduction Cryo-electron microscopy (cryo-EM) is an emerging experimental method to characterize the structure of large biomolecular assemblies. Single particle cryo-EM records 2D images (so-called micrographs) of projections of the three-dimensional particle, which need to be processed to obtain the threedimensional reconstruction. A crucial step in the reconstruction process is particle picking which involves detection of particles in noisy 2D micrographs with low signal-to-noise ratios of typically 1:10 or even lower. Typically, each picture contains a large number of particles, and particles have unknown irregular and nonconvex shapes.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Learning/Statistics & Optimisation
Brain Computer Interfaces
Theory & Algorithms
ID Code:8672
Deposited By:Bernhard Schölkopf
Deposited On:18 February 2012