Evidence map›Paper›PMID 22696407›Full record

ReviewBiopolymers2012

Macromolecular structure modeling from 3D EM using VolRover 2.0.

Qin Zhang, Radhakrishna Bettadapura, Chandrajit Bajaj

Abstract readReview
In one paragraph

Review in Biopolymers, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. NONUNIFORM FOURIER TRANSFORMS FOR RIGID-BODY AND MULTI-DIMENSIONAL ROTATIONAL CORRELATIONS.SIAM journal on scientific computing : a publication of the Society for Industrial and Applied Mathematics · 2013
    Article
  10. Article
  11. Shape-based regularization of electron tomographic reconstruction.IEEE transactions on medical imaging · 2012
    Article
  12. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Qin ZhangInstitute for Computational Engineering and Sciences, The University of Texas, Austin, TX 78712, USA.
Radhakrishna Bettadapura
Chandrajit Bajaj

Funding

Software Maintenance for Biomolecular ComplexesR01EB004873 · NIBIB · UNIVERSITY OF TEXAS AT AUSTIN · PI BAJAJ, CHANDRAJIT L · 2007 to 2010
$1.2M
Hierarchical Methods for Large BioMolecular ComplexesR01GM074258 · NIGMS · UNIVERSITY OF TEXAS AUSTIN · PI BAJAJ, CHANDRAJIT L · 2005 to 2010
$778k
NIBIB NIH HHS R01 EB004873NIBIB NIH HHS R01-EB004873NIGMS NIH HHS R01 GM074258
6 · The paper itself

Abstract

We review tools for structure identification and model-based refinement from three-dimensional electron microscopy implemented in our in-house software package, VOLROVER 2.0. For viral density maps with icosahedral symmetry, we segment the capsid, polymeric, and monomeric subunits using techniques based on automatic symmetry detection and multidomain fast marching. For large biomolecules without symmetry information, we again use our multidomain fast-marching method with manual or fit-based multiseeding to segment meaningful substructures. In either case, we subject the resulting segmented subunit to secondary structure detection when the EM resolution is sufficiently high, and rigid-body structure fitting when the corresponding X-ray structure is available. Secondary structure elements are identified by three techniques: our earlier volume-based and boundary-based skeletonization methods as well as a new method, currently in development, based on solving the grassfire flow equation. For rigid-body fitting, we adapt our earlier fast Fourier-based correlation scheme F2Dock. Our reported segmentation, secondary structure elements identification, and rigid-body fitting techniques, implemented in VOLROVER 2.0 are applied to the PSB 2011 cryo-EM modeling challenge data, and our results are briefly compared to similar results submitted from other research groups. The comparisons show that our techniques are equally capable of segmenting relatively accurate subunits from a viral or protein assembly, and that high segmentation quality leads in turn to higher-quality results of secondary structure elements identification and correlation-based rigid-body fitting. © 2012 Wiley Periodicals, Inc. Biopolymers 97: 709-731, 2012.

Indexed as

Models, MolecularSoftwareChaperonin 10Chaperonin 60Cryoelectron MicroscopyProteinsProtein Structure, SecondaryRibosomesChaperonin 10Chaperonin 60Proteins

Identifiers

PMID22696407
PMCPMC3511818

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.