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1.
J Struct Biol ; 198(2): 124-133, 2017 05.
Article in English | MEDLINE | ID: mdl-28344036

ABSTRACT

We present a new software package called Focus that interfaces cryo-transmission electron microscopy (cryo-EM) data collection with computer image processing. Focus creates a user-friendly environment to import and manage data recorded by direct electron detectors and perform elemental image processing tasks in a high-throughput manner while new data is being acquired at the microscope. It provides the functionality required to remotely monitor the progress of data collection and data processing, which is essential now that automation in cryo-EM allows a steady flow of images of single particles, two-dimensional crystals, or electron tomography data to be recorded in overnight sessions. The rapid detection of any errors that may occur greatly increases the productivity of recording sessions at the electron microscope.


Subject(s)
Cryoelectron Microscopy/methods , Image Processing, Computer-Assisted/methods , Software , Automation , Signal-To-Noise Ratio , User-Computer Interface
2.
J Struct Biol ; 173(2): 365-74, 2011 Feb.
Article in English | MEDLINE | ID: mdl-20868753

ABSTRACT

We have built and extensively tested a tool-chain to prepare and screen two-dimensional crystals of membrane proteins by transmission electron microscopy (TEM) at room temperature. This automated process is an extension of a new procedure described recently that allows membrane protein 2D crystallization in parallel (Iacovache et al., 2010). The system includes a gantry robot that transfers and prepares the crystalline solutions on grids suitable for TEM analysis and an entirely automated microscope that can analyze 96 grids at once without human interference. The operation of the system at the user level is solely controlled within the MATLAB environment: the commands to perform sample handling (loading/unloading in the microscope), microscope steering (magnification, focus, image acquisition, etc.) as well as automatic crystal detection have been implemented. Different types of thin samples can efficiently be screened provided that the particular detection algorithm is adapted to the specific task. Hence, operating time can be shared between multiple users. This is a major step towards the integration of transmission electron microscopy into a high throughput work-flow.


Subject(s)
Crystallization/methods , Microscopy, Electron, Transmission/methods , Membrane Proteins/chemistry , Membrane Proteins/ultrastructure
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