Public Datasets

h1. Public Data Sets: GroEL I

h2. 1. Images.

Images were acquired with a FEI Tecnai F20 equipped with a 2Kx2K CCD Tietz camera, as defocal pairs at a nominal magnification of 62,000 x and a voltage of 120 KeV, using the Leginon system (Potter et al., 1999; Carragher et al., 2000). The first image (named *.001.mrc) is acquired at near to focus (NTF) conditions (-0.6 to -1.5 µm) and the second image (named *.002.mrc) at farther from focus (FFF) conditions (-3µm). The time interval between the two exposures is approximately 20s due to the time required to read out the digital image from the camera. The pixel size is 2.238 Å at the specimen scale and the accumulated dose for each high magnification image area was ~10 e/Ų. 

Below is an example of a defocus pair. Click on the images to see at full scale.

p=. (a) !fig1a_full.jpg!:http://emg.nysbc.org/prtl_data/groel_10k/fig1a_full.jpg           (b) !fig1b_full.jpg!:http://emg.nysbc.org/prtl_data/groel_10k/fig1b_full.jpg

(a) Near to focus (NTF) image. (b) Far from focus - FFF image. 

p=. *Figure 1: An example pair of high magnification images of GroEL.*

*Downloading High Magnification Images:* Image files are provided in "MRC":http://emg.nysbc.org/prtl_data/mrc_specification.htm format and as JPEG files

Download entire set of images using a tool called [[dbemwiz|Dbemwiz]], and use section name "03oct09b". 

We suggest using a tool called "em2em":http://www.imagescience.de/em2em, to convert MRC files to other formats.

h2. 2.1 Automated Picking:

A two-stage approach was applied for automatic selection of GroEL particles. In the first stage, a set of candidate particles were automatically selected for each micrograph using the fast local correlation algorithm (Roseman, 2003) combined with a peak searching and thresholding algorithms. In the second stage, the set of candidate particles were filtered with a clutter finder to reject contamination (Zhu et al., 2004). The clutter finder starts with edge detection followed by connected component labeling, convex hull computation, and size filtering. Particle coordinates are provide below:

"Coordinates of 16212 side-view":http://emg.nysbc.org/prtl_data/groel_10k/03oct09b.side.0.41.tar and "10603 top-view":http://emg.nysbc.org/prtl_data/groel_10k/03oct09b.top.0.39.tar GroEL particles selected in the FFF images. [Need a description of the coordinate file – the link is missing in the pages at the moment]

h2. 3. 3D Reconstructed Map

A set of 7505 particles were extracted from a set of 141 NTF micrographs whose corresponding FFF micrographs contain the first 7,505 particles of the automatically selected 16216 side-view particles. This particle set was used to create a 3D reconstruction using D7 point-group symmetry and 9 cycles of refinement. 

"Coordinates":http://emg.nysbc.org/prtl_data/klh/klh_10k/prtl_in_3dmap.tar of 7,505 side-view particles contributing to the map. 

Table 2: Sample reconstruction using 7,505 side-view particles. 

|*Three-dimensional Density Map (click on the images to download the map)*|*Description of Reconstruction Procedures*|*Comments*|

|!groel_160.jpg!:http://emg.nysbc.org/prtl_data/groel_10k/groel_7k_map.mrc.gz !groel_160_top.jpg!:http://emg.nysbc.org/prtl_data/groel_10k/groel_7k_map.mrc.gz|The reconstruction was produced using EMAN (Ludtke et al, 1999) with a D7 symmetry being imposed. The set of 7,505 side-view particles was subjected to 9 cycles of refinement, using a previous volume as a reference, and a new reconstruction volume was calculated.|The set of 7505 particls were extracted from a set of 141 NTF micrographs whose corresponding FFF micrographs contain the first 7,505 particles of the above 16216 side-view particles.|

h2. 5. References 

 # Carragher, B., Kisseberth, N., Kriegman, D., Milligan, R. A., Potter, C. S., Pulokas, J., and Reilein, A. (2000) Leginon: An automated system for acquisition of images from vitreous ice specimens. J. Struct. Biol. 132: 33-45. 

 # Ludtke, S.J., P.R. Baldwin, and W. Chiu. (1999) EMAN: Semiautomated software for high-resolution single-particle reconstructions. J. Struct. Biol. 128: 82-97. 

 # Roseman, A.M. (2003) Particle finding in electron micrographs using a fast local correlation algorithm. Ultramicroscopy 94: 225-236. 

 # Zhu, Y., B. Carragher, D.J. Kriegman, R. Milligan, and C.S. Potter. (2001) Automated identification of filaments in cryo-electron microscopy images. J. Struct. Biol. 135: 302-312. 

 # Zhu, Y., Carragher, B., and Potter, C. S. (2004) Contaminant detection: improving tempalte matching based particle selection for cryo-electron microscopy. In: Proceedings of IEEE International Symposium on Biomedical Imaging, pp. 1071-1074, April 15-18, 2004, Arlington, VA.