Document Type

Article

Publication Date

2013

DOI

10.1109/TCBB.2013.121

Publication Title

IEEE-ACM Transactions on Computational Biology and Bioinformatics

Volume

10

Issue

5

Pages

1289-1298

Abstract

Cryo-electron microscopy is an experimental technique that is able to produce 3D gray-scale images of protein molecules. In contrast to other experimental techniques, cryo-electron microscopy is capable of visualizing large molecular complexes such as viruses and ribosomes. At medium resolution, the positions of the atoms are not visible and the process cannot proceed. The medium-resolution images produced by cryo-electron microscopy are used to derive the atomic structure of the proteins in de novo modeling. The skeletons of the 3D gray-scale images are used to interpret important information that is helpful in de novo modeling. Unfortunately, not all features of the image can be captured using a single segmentation. In this paper, we present a segmentation-free approach to extract the gray-scale curve-like skeletons. The approach relies on a novel representation of the 3D image, where the image is modeled as a graph and a set of volume trees. A test containing 36 synthesized maps and one authentic map shows that our approach can improve the performance of the two tested tools used in de novo modeling. The improvements were 62 and 13 percent for Gorgon and DP-TOSS, respectively.

Comments

NOTE: This is the author's post-print version of a work that was published in IEEE-ACM Transactions on Computational Biology and Bioinformatics. The final version was published as:

Al Nasr, K., Liu, C. M., Rwebangira, M., Burge, L., & He, J. (2013). Intensity-based skeletonization of CryoEM gray-scale images using a true segmentation-free algorithm. Ieee-Acm Transactions on Computational Biology and Bioinformatics, 10(5), 1289-1298. doi:10.1109/tcbb.2013.121

Available at: http://dx.doi.org/10.1109/tcbb.2013.121

Original Publication Citation

Al Nasr, K., Liu, C. M., Rwebangira, M., Burge, L., & He, J. (2013). Intensity-based skeletonization of CryoEM gray-scale images using a true segmentation-free algorithm. Ieee-Acm Transactions on Computational Biology and Bioinformatics, 10(5), 1289-1298. doi:10.1109/tcbb.2013.121

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