The Experts below are selected from a list of 191127 Experts worldwide ranked by ideXlab platform
Thomas C. Terwilliger - One of the best experts on this subject based on the ideXlab platform.
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map segmentation Automated Model building and their application to the cryo em Model challenge
Journal of Structural Biology, 2018Co-Authors: Thomas C. Terwilliger, Paul D. Adams, Pavel V Afonine, Oleg V SobolevAbstract:Abstract A recently-developed method for identifying a compact, contiguous region representing the unique part of a density map was applied to 218 Cryo-EM maps with resolutions of 4.5 A or better. The key elements of the segmentation procedure are (1) identification of all regions of density above a threshold and (2) choice of a unique set of these regions, taking symmetry into consideration, that maximize connectivity and compactness. This segmentation approach was then combined with tools for Automated map sharpening and Model-building to generate Models for the 12 maps in the 2016 Cryo-EM Model Challenge in a fully Automated manner. The resulting Models have completeness from 24% to 82% and RMS distances from reference interpretations of 0.6 A–2.1 A.
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map segmentation Automated Model building and their application to the cryo em Model challenge
bioRxiv, 2018Co-Authors: Thomas C. Terwilliger, Paul D. Adams, Pavel V Afonine, Oleg V SobolevAbstract:A recently-developed method for identifying a compact, contiguous region representing the unique part of a density map was applied to 218 cryo-EM maps with resolutions of 4.5 A or better. The key elements of the segmentation procedure are (1) identification of all regions of density above a threshold and (2) choice of a unique set of these regions, taking symmetry into consideration, that maximize connectivity and compactness. This segmentation approach was then combined with tools for Automated map sharpening and Model-building to generate Models for the 12 maps in the 2016 cryo-EM Model challenge in a fully Automated manner. The resulting Models have completeness from 24% to 82% and rms differences from reference interpretations of 0.6 A to 2.1 A.
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macromolecular x ray structure determination using weak single wavelength anomalous data
Nature Methods, 2015Co-Authors: Gabor Bunkoczi, Paul D. Adams, Randy J. Read, Airlie J Mccoy, Nathaniel Echols, Ralf W Grossekunstleve, James M Holton, Thomas C. TerwilligerAbstract:We describe a likelihood-based method for determining the substructure of anomalously scattering atoms in macromolecular crystals that allows successful structure determination by single-wavelength anomalous diffraction (SAD) X-ray analysis with weak anomalous signal. With the use of partial Models and electron density maps in searches for anomalously scattering atoms, testing of alternative values of parameters and parallelized Automated Model-building, this method has the potential to extend the applicability of the SAD method in challenging cases.
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application of den refinement and Automated Model building to a difficult case of molecular replacement phasing the structure of a putative succinyl diaminopimelate desuccinylase from corynebacterium glutamicum
Acta Crystallographica Section D-biological Crystallography, 2012Co-Authors: Paul D. Adams, Randy J. Read, Thomas C. Terwilliger, Axel T Brunger, Debanu Das, Ashley M Deacon, Joanna C Grant, Michael Levitt, Gunnar F SchroderAbstract:Phasing by molecular replacement remains difficult for targets that are far from the search Model or in situations where the crystal diffracts only weakly or to low resolution. Here, the process of determining and refining the structure of Cgl1109, a putative succinyl-diaminopimelate desuccinylase from Corynebacterium glutamicum, at ∼3 A resolution is described using a combination of homology Modeling with ModelLER, molecular-replacement phasing with Phaser, deformable elastic network (DEN) refinement and Automated Model building using AutoBuild in a semi-Automated fashion, followed by final refinement cycles with phenix.refine and Coot. This difficult molecular-replacement case illustrates the power of including DEN restraints derived from a starting Model to guide the movements of the Model during refinement. The resulting improved Model phases provide better starting points for Automated Model building and produce more significant difference peaks in anomalous difference Fourier maps to locate anomalous scatterers than does standard refinement. This example also illustrates a current limitation of Automated procedures that require manual adjustment of local sequence misalignments between the homology Model and the target sequence.
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solve and resolve Automated structure solution density modification and Model building
Journal of Synchrotron Radiation, 2004Co-Authors: Thomas C. TerwilligerAbstract:The software SOLVE and RESOLVE can carry out all the steps in macromolecular structure solution, from scaling and heavy-atom location through phasing, density modification and Model-building in the MAD, SAD and MIR cases. SOLVE uses scoring scheme to convert the decision-making in macromolecular structure solution to an optimization problem. RESOLVE carries out the identification of NCS, density modification and Automated Model-building. The procedure is fully Automated and can function at resolutions as low as 3 A.
Alfred O Hero - One of the best experts on this subject based on the ideXlab platform.
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phase transitions and a Model order selection criterion for spectral graph clustering
IEEE Transactions on Signal Processing, 2018Co-Authors: Pinyu Chen, Alfred O HeroAbstract:One of the longstanding open problems in spectral graph clustering (SGC) is the so-called Model order selection problem: Automated selection of the correct number of clusters. This is equivalent to the problem of finding the number of connected components or communities in an undirected graph. We propose an Automated Model order selection (AMOS), a solution to the SGC Model selection problem under a random interconnection Model using a novel selection criterion that is based on an asymptotic phase transition analysis. AMOS can more generally be applied to discovering hidden block diagonal structure in symmetric non-negative matrices. Numerical experiments on simulated graphs validate the phase transition analysis, and real-world network data are used to validate the performance of the proposed Model selection procedure.
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amos an Automated Model order selection algorithm for spectral graph clustering
International Conference on Acoustics Speech and Signal Processing, 2017Co-Authors: Pinyu Chen, Thibaut Gensollen, Alfred O HeroAbstract:One of the longstanding problems in spectral graph clustering (SGC) is the so-called Model order selection problem: Automated selection of the correct number of clusters. This is equivalent to the problem of finding the number of connected components or communities in an undirected graph. In this paper, we propose AMOS, an Automated Model order selection algorithm for SGC. Based on a recent analysis of clustering reliability for SGC under the random interconnection Model, AMOS works by incrementally increasing the number of clusters, estimating the quality of identified clusters, and providing a series of clustering reliability tests. Consequently, AMOS outputs clusters of minimal Model order with statistical clustering reliability guarantees. Comparing to three other Automated graph clustering methods on real-world datasets, AMOS shows superior performance in terms of multiple external and internal clustering metrics.
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phase transitions and a Model order selection criterion for spectral graph clustering
arXiv: Social and Information Networks, 2016Co-Authors: Pinyu Chen, Alfred O HeroAbstract:One of the longstanding open problems in spectral graph clustering (SGC) is the so-called Model order selection problem: Automated selection of the correct number of clusters. This is equivalent to the problem of finding the number of connected components or communities in an undirected graph. We propose Automated Model order selection (AMOS), a solution to the SGC Model selection problem under a random interconnection Model (RIM) using a novel selection criterion that is based on an asymptotic phase transition analysis. AMOS can more generally be applied to discovering hidden block diagonal structure in symmetric non-negative matrices. Numerical experiments on simulated graphs validate the phase transition analysis, and real-world network data is used to validate the performance of the proposed Model selection procedure.
Michael S Samoilov - One of the best experts on this subject based on the ideXlab platform.
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Temperature control of fimbriation circuit switch in uropathogenic Escherichia coli: Quantitative analysis via Automated Model abstraction
2016Co-Authors: Hiroyuki Kuwahara, Chris J Myers, Michael S SamoilovAbstract:Uropathogenic Escherichia coli (UPEC) represent the predominant cause of urinary tract infections (UTIs). A key UPEC molecular virulence mechanism is type 1 fimbriae, whose expression is controlled by the orientation of an invertible chromosomal DNA element—the fim switch. Temperature has been shown to act as a major regulator of fim switching behavior and is overall an important indicator as well as functional feature of many urologic diseases, including UPEC host-pathogen interaction dynamics. Given this panoptic physiological role of temperature during UTI progression and notable empirical challenges to its direct in vivo studies, in silico Modeling of corresponding biochemical and biophysical mechanisms essential to UPEC pathogenicity may significantly aid our understanding of the underlying disease processes. However, rigorous computational analysis of biological systems, such as fim switch temperature control circuit, has hereto presented a notoriously demanding problem due to both the substantial complexity of the gene regulatory networks involved as well as their often characteristically discrete and stochastic dynamics. To address these issues, we have developed an approach that enables Automated multiscale abstraction of biological system descriptions based on reaction kinetics. Implemented as a computational tool, this method has allowed us to efficiently analyze the modular organization and behavior of the E. coli fimbriation switch circuit at different temperature settings, thus facilitating new insights into this mode of UPEC molecular virulence regulation. In particular, our results suggest that, with respect to its role in shuttin
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temperature control of fimbriation circuit switch in uropathogenic escherichia coli quantitative analysis via Automated Model abstraction
PLOS Computational Biology, 2010Co-Authors: Hiroyuki Kuwahara, Chris J Myers, Michael S SamoilovAbstract:Uropathogenic Escherichia coli (UPEC) represent the predominant cause of urinary tract infections (UTIs). A key UPEC molecular virulence mechanism is type 1 fimbriae, whose expression is controlled by the orientation of an invertible chromosomal DNA element—the fim switch. Temperature has been shown to act as a major regulator of fim switching behavior and is overall an important indicator as well as functional feature of many urologic diseases, including UPEC host-pathogen interaction dynamics. Given this panoptic physiological role of temperature during UTI progression and notable empirical challenges to its direct in vivo studies, in silico Modeling of corresponding biochemical and biophysical mechanisms essential to UPEC pathogenicity may significantly aid our understanding of the underlying disease processes. However, rigorous computational analysis of biological systems, such as fim switch temperature control circuit, has hereto presented a notoriously demanding problem due to both the substantial complexity of the gene regulatory networks involved as well as their often characteristically discrete and stochastic dynamics. To address these issues, we have developed an approach that enables Automated multiscale abstraction of biological system descriptions based on reaction kinetics. Implemented as a computational tool, this method has allowed us to efficiently analyze the modular organization and behavior of the E. coli fimbriation switch circuit at different temperature settings, thus facilitating new insights into this mode of UPEC molecular virulence regulation. In particular, our results suggest that, with respect to its role in shutting down fimbriae expression, the primary function of FimB recombinase may be to effect a controlled down-regulation (rather than increase) of the ON-to-OFF fim switching rate via temperature-dependent suppression of competing dynamics mediated by recombinase FimE. Our computational analysis further implies that this down-regulation mechanism could be particularly significant inside the host environment, thus potentially contributing further understanding toward the development of novel therapeutic approaches to UPEC-caused UTIs.
Tobias Klinder - One of the best experts on this subject based on the ideXlab platform.
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Automated Model based vertebra detection identification and segmentation in ct images
Medical Image Analysis, 2009Co-Authors: Tobias Klinder, Jorn Ostermann, Matthias Ehm, Astrid Franz, Reinhard Kneser, Cristian LorenzAbstract:Abstract For many orthopaedic, neurological, and oncological applications, an exact segmentation of the vertebral column including an identification of each vertebra is essential. However, although bony structures show high contrast in CT images, the segmentation and labelling of individual vertebrae is challenging. In this paper, we present a comprehensive solution for automatically detecting, identifying, and segmenting vertebrae in CT images. A framework has been designed that takes an arbitrary CT image, e.g., head-neck, thorax, lumbar, or whole spine, as input and provides a segmentation in form of labelled triangulated vertebra surface Models. In order to obtain a robust processing chain, profound prior knowledge is applied through the use of various kinds of Models covering shape, gradient, and appearance information. The framework has been tested on 64 CT images even including pathologies. In 56 cases, it was successfully applied resulting in a final mean point-to-surface segmentation error of 1.12 ± 1.04 mm. One key issue is a reliable identification of vertebrae. For a single vertebra, we achieve an identification success of more than 70%. Increasing the number of available vertebrae leads to an increase in the identification rate reaching 100% if 16 or more vertebrae are shown in the image.
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Automated Model based rib cage segmentation and labeling in ct images
Medical Image Computing and Computer-Assisted Intervention, 2007Co-Authors: Tobias Klinder, Cristian Lorenz, Jens Von Berg, Sebastian Peter Michael Dries, Thomas Bulow, Jorn OstermannAbstract:We present a new Model-based approach for an Automated labeling and segmentation of the rib cage in chest CT scans. A mean rib cage Model including a complete vertebral column is created out of 29 data sets. We developed a ray search based procedure for rib cage detection and initial Model pose. After positioning the Model, it was adapted to 18 unseen CT data. In 16 out of 18 data sets, detection, labeling, and segmentation succeeded with a mean segmentation error of less than 1.3 mm between true and detected object surface. In one case the rib cage detection failed, in another case the Automated labeling.
Paul D. Adams - One of the best experts on this subject based on the ideXlab platform.
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map segmentation Automated Model building and their application to the cryo em Model challenge
Journal of Structural Biology, 2018Co-Authors: Thomas C. Terwilliger, Paul D. Adams, Pavel V Afonine, Oleg V SobolevAbstract:Abstract A recently-developed method for identifying a compact, contiguous region representing the unique part of a density map was applied to 218 Cryo-EM maps with resolutions of 4.5 A or better. The key elements of the segmentation procedure are (1) identification of all regions of density above a threshold and (2) choice of a unique set of these regions, taking symmetry into consideration, that maximize connectivity and compactness. This segmentation approach was then combined with tools for Automated map sharpening and Model-building to generate Models for the 12 maps in the 2016 Cryo-EM Model Challenge in a fully Automated manner. The resulting Models have completeness from 24% to 82% and RMS distances from reference interpretations of 0.6 A–2.1 A.
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map segmentation Automated Model building and their application to the cryo em Model challenge
bioRxiv, 2018Co-Authors: Thomas C. Terwilliger, Paul D. Adams, Pavel V Afonine, Oleg V SobolevAbstract:A recently-developed method for identifying a compact, contiguous region representing the unique part of a density map was applied to 218 cryo-EM maps with resolutions of 4.5 A or better. The key elements of the segmentation procedure are (1) identification of all regions of density above a threshold and (2) choice of a unique set of these regions, taking symmetry into consideration, that maximize connectivity and compactness. This segmentation approach was then combined with tools for Automated map sharpening and Model-building to generate Models for the 12 maps in the 2016 cryo-EM Model challenge in a fully Automated manner. The resulting Models have completeness from 24% to 82% and rms differences from reference interpretations of 0.6 A to 2.1 A.
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macromolecular x ray structure determination using weak single wavelength anomalous data
Nature Methods, 2015Co-Authors: Gabor Bunkoczi, Paul D. Adams, Randy J. Read, Airlie J Mccoy, Nathaniel Echols, Ralf W Grossekunstleve, James M Holton, Thomas C. TerwilligerAbstract:We describe a likelihood-based method for determining the substructure of anomalously scattering atoms in macromolecular crystals that allows successful structure determination by single-wavelength anomalous diffraction (SAD) X-ray analysis with weak anomalous signal. With the use of partial Models and electron density maps in searches for anomalously scattering atoms, testing of alternative values of parameters and parallelized Automated Model-building, this method has the potential to extend the applicability of the SAD method in challenging cases.
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application of den refinement and Automated Model building to a difficult case of molecular replacement phasing the structure of a putative succinyl diaminopimelate desuccinylase from corynebacterium glutamicum
Acta Crystallographica Section D-biological Crystallography, 2012Co-Authors: Paul D. Adams, Randy J. Read, Thomas C. Terwilliger, Axel T Brunger, Debanu Das, Ashley M Deacon, Joanna C Grant, Michael Levitt, Gunnar F SchroderAbstract:Phasing by molecular replacement remains difficult for targets that are far from the search Model or in situations where the crystal diffracts only weakly or to low resolution. Here, the process of determining and refining the structure of Cgl1109, a putative succinyl-diaminopimelate desuccinylase from Corynebacterium glutamicum, at ∼3 A resolution is described using a combination of homology Modeling with ModelLER, molecular-replacement phasing with Phaser, deformable elastic network (DEN) refinement and Automated Model building using AutoBuild in a semi-Automated fashion, followed by final refinement cycles with phenix.refine and Coot. This difficult molecular-replacement case illustrates the power of including DEN restraints derived from a starting Model to guide the movements of the Model during refinement. The resulting improved Model phases provide better starting points for Automated Model building and produce more significant difference peaks in anomalous difference Fourier maps to locate anomalous scatterers than does standard refinement. This example also illustrates a current limitation of Automated procedures that require manual adjustment of local sequence misalignments between the homology Model and the target sequence.
