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A Graph Approach to Bridge the Gaps in Volumetric Electron Cryo-microscopy Skeletons

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Bioinformatics Research and Applications (ISBRA 2013)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 7875))

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Abstract

Electron Cryo-microscopy is an advanced imaging technique that is able to produce volumetric images of proteins that are large or hard to crystallize. De novo modeling is a process that aims at deriving the structure of the protein using the images produced by Electron Cryo-microscopy. At the medium resolutions (5 to 10Å), the location and orientation of the secondary structure elements can be computationally identified on the images. However, there is no registration between the detected secondary structure elements and the protein sequence, and therefore it is challenging to derive the atomic structure from such volume data. The skeleton of the volume image is used to interpret the connections between the secondary structure elements in order to reduce the search space of the registration problem. Unfortunately, not all features of the image can be captured using a single segmentation. Moreover, the skeleton is sensitive to the threshold used which leads to gaps in the skeleton. In this paper, we present a threshold-independent approach to overcome the problem of gaps in the skeletons. The approach uses a novel representation of the image where the image is modeled as a graph and a set of volume trees. A test containing thirteen synthesized images and two authentic images showed that our approach could improve the existent skeletons. The percent of improvement achieved were 117% and 40% for Gorgon and MapEM, respectively.

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Author information

Authors and Affiliations

  1. Department of Systems and Computer Science, Howard University, Washington, DC, 20059, USA

    Kamal Al Nasr, Chunmei Liu, Mugizi Robert Rwebangira & Legand L. Iii Burge

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  1. Kamal Al Nasr
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  2. Chunmei Liu
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  3. Mugizi Robert Rwebangira
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  4. Legand L. Iii Burge
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Editor information

Editors and Affiliations

  1. Computer Science, Georgia State University, 34 Peachtree Street, Suite 1410, 30303, Atlanta, GA, USA

    Zhipeng Cai

  2. Computer Science, Iowa State University, 50011, Ames, IA, USA

    Oliver Eulenstein

  3. Bioinformatics and Genomics, University of North Carolina at Charlotte, 9201 University City Blvd, Suite 315, 28223, Charlotte, NC, USA

    Daniel Janies

  4. Physiology and Neurobiology, University of Connecticut, 75 North Eagleville Road, Unit 3156, 06269, Storrs, CT, USA

    Daniel Schwartz

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Nasr, K.A., Liu, C., Rwebangira, M.R., Burge, L.L.I. (2013). A Graph Approach to Bridge the Gaps in Volumetric Electron Cryo-microscopy Skeletons. In: Cai, Z., Eulenstein, O., Janies, D., Schwartz, D. (eds) Bioinformatics Research and Applications. ISBRA 2013. Lecture Notes in Computer Science(), vol 7875. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38036-5_22

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  • DOI: https://doi.org/10.1007/978-3-642-38036-5_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38035-8

  • Online ISBN: 978-3-642-38036-5

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