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PyTom | Python and Tomography

Skip to primary content. Skip to secondary content. PyTom provides the essential tools for the analysis of subtomograms obtained by cryo electron tomography. It covers a processing pipeline of tomogram reconstruction. Of macromolecular complexes in tomograms, fine alignment. Of subtomograms extracted at these locations and their classification. PyTom is mostly written in Python. At the Max Planck Institute for Biochemistry, but we highly encourage developers to contribute to PyTom on an open source basis.

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Skip to primary content. Skip to secondary content. PyTom provides the essential tools for the analysis of subtomograms obtained by cryo electron tomography. It covers a processing pipeline of tomogram reconstruction. Of macromolecular complexes in tomograms, fine alignment. Of subtomograms extracted at these locations and their classification. PyTom is mostly written in Python. At the Max Planck Institute for Biochemistry, but we highly encourage developers to contribute to PyTom on an open source basis.
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PyTom | Python and Tomography | pytom.org Reviews

https://pytom.org

Skip to primary content. Skip to secondary content. PyTom provides the essential tools for the analysis of subtomograms obtained by cryo electron tomography. It covers a processing pipeline of tomogram reconstruction. Of macromolecular complexes in tomograms, fine alignment. Of subtomograms extracted at these locations and their classification. PyTom is mostly written in Python. At the Max Planck Institute for Biochemistry, but we highly encourage developers to contribute to PyTom on an open source basis.

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1

PyTom: Align subtomograms

http://pytom.org/doc/pytom/alignment.html

Old" Expectation-Maximization based Real Space Alignment. This alignment algorithm was the default until 2015 and originally published in Hrabe et al, JSB 2012. New" Real Space Alignment. To incorporate Gold Standard FSC for resolution determination and filtering of iteratively improved averages we re-engineered the alignment algorithm in 2015. The usage from the command line is greatly simplified, but currently no GUI support is provided.

2

Align Projections and reconstruct tomograms

http://pytom.org/doc/pytom/reconstructTomograms.html

PyTom: Align projections and reconstruct a tomogram. Pytom currently supports the alignment of projections by fiducials and reconstruction by weighted backprojection. Both, alignment by gold beads and reonstruction by weighted backprojection are still the most common approaches in the field. Nevertheless, we are working on the implementation of further alignment and reconstruction methods. Alignment of tilt series. The PyTom alignment function simply minimizes the residual error of the coordinates projec...

3

PyTom: Classify aligned particles

http://pytom.org/doc/pytom/classification.html

PyTom: Classify aligned particles. The aim of classification is to group structurally different particles that are part of a particle list into different bins. You may want to use classification directly after localization to discard obvious false positives or 'bad' particles or you may want to classify subtomograms after alignment to get some insights into possible conformational hetergeneity of your molecules of interest. Calculate correlation matrix.py. The CCC matrix is computed using the script.

4

PyTom: Localize Macromolecules

http://pytom.org/doc/pytom/localization.html

PyTom: Localize Macromolecules by template matching. Features in a tomogram that resemble a structural 'template' can be localized in an automated fashion using 'template matching'. In this approach a 3D template is correlated with a given tomogram. In this procedure the different possible rotations and translations are sampled exhaustively using the algorithm described in Förster et al, Meth. Enzymol. 483:215-43 (2010). You will find sample localization scripts in the tutorial repository in the. Mpirun ...

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Award Winners | Heinz Billing Prize for the Advancement of scientific computing

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Skip to navigation (Press Enter). Skip to main content (Press Enter). Heinz Billing Award 2015. Heinz Billing Award 2015. The Winners of the Heinz Billing Award. 1993 Dr. Hans Thomas Janka, Dr. Ewald Müller, Dr. Maximilian Ruffert. Max-Planck-Institut für Astrophysik, Garching. Simulation turbulenter Konvektion in Supernova-Explosionen in massereichen Sternen. 1994 Dr. Rainer Goebel. Max-Planck-Institut für Hirnforschung, Frankfurt. Neurolator - Ein Programm zur Simulation neuronaler Netzwerke. 2001 Dr&#...

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