Erratum to: Graph-based deformable matching of 3D line segments with application in protein fitting

Dou, Hang; Baker, Matthew L.; Ju, Tao

doi:10.1007/s00371-015-1133-8

Cited by 2 publications

(4 citation statements)

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“…Corresponding helices should have similar lengths, close-by helices in the model should match to close-by helices in the map, and the matching should correspond to a deformation of the model that is as rigid as possible. These goals can be formulated either as a clique-finding problem (39) or a graph-matching problem (36). We use the recent graph-matching method (36), which is both more efficient and accurate.…”

Section: Preparing For Fittingmentioning

confidence: 99%

“…These goals can be formulated either as a clique-finding problem (39) or a graph-matching problem (36). We use the recent graph-matching method (36), which is both more efficient and accurate. An example result is shown in Fig.…”

Section: Preparing For Fittingmentioning

confidence: 99%

“…Our method builds upon robust methods for detecting a-helices from cryo-EM maps at intermediate resolutions (35) and for matching them with those in a template structure (36). We incorporate the helix guidance within a quadratic energy function, adapted from the computer animation community (37), which penalizes nonaffine distortion of the protein backbone.…”

Section: Introductionmentioning

confidence: 99%

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Flexible Fitting of Atomic Models into Cryo-EM Density Maps Guided by Helix Correspondences

Dou

Burrows

Baker

et al. 2017

Biophysical Journal

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Although electron cryo-microscopy (cryo-EM) has recently achieved resolutions of better than 3 Å, at which point molecular modeling can be done directly from the density map, analysis and annotation of a cryo-EM density map still primarily rely on fitting atomic or homology models to the density map. In this article, we present, to our knowledge, a new method for flexible fitting of known or modeled protein structures into cryo-EM density maps. Unlike existing methods that are guided by local density gradients, our method is guided by correspondences between the α-helices in the density map and model, and does not require an initial rigid-body fitting step. Compared with current methods on both simulated and experimental density maps, our method not only achieves greater accuracy for proteins with large deformations but also runs as fast or faster than many of the other flexible fitting routines.

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Section: Preparing For Fittingmentioning

confidence: 99%

Section: Preparing For Fittingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Flexible Fitting of Atomic Models into Cryo-EM Density Maps Guided by Helix Correspondences

Dou

Burrows

Baker

et al. 2017

Biophysical Journal

Self Cite

View full text Add to dashboard Cite

show abstract

“…The paper by Dou et al [21] is about non-rigid registration; the one by Wang et al [22] focuses on the problem of 3D object tracking in videos and the paper by Getto et al [23] is about medical image segmentation.…”

Section: Articles In This Issuementioning

confidence: 99%