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EMDataBank.org: unified data resource for CryoEM

C. L. Lawson, M. L. Baker, C. Best, C. Bi, M. Dougherty, P. Feng, G. van Ginkel, B. Devkota, I. Lagerstedt, S. J. Ludtke, R. H. Newman, T. J. Oldfield (+10 others)
2010 Nucleic Acids Research  
global 'one-stop shop' resource for deposition and retrieval of cryoEM maps, models and associated metadata.  ...  The resource unifies public access to the two major archives containing EM-based structural data: EM Data Bank (EMDB) and Protein Data Bank (PDB), and facilitates use of EM structural data of macromolecules  ...  ACKNOWLEDGEMENTS We are grateful to Tom Goddard for integrating the EMDataBank.org web service into UCSF Chimera. Conflict of interest statement. None declared.  ... 
doi:10.1093/nar/gkq880 pmid:20935055 pmcid:PMC3013769 fatcat:ipujineisngezfbkud2ltei7eq

Unified Data Resource for Cryo-EM [chapter]

Catherine L. Lawson
2010 Methods in Enzymology  
a "one-stop shop" resource for global deposition and retrieval of cryoEM map, model and associated metadata.  ...  The resource unifies public access to the two major EM Structural Data archives: EM Data Bank (EMDB) and Protein Data Bank (PDB), and facilitates use of EM structural data of macromolecules and macromolecular  ...  The Unified Data Resource for CryoEM (EMDataBank.org) was created in order to unify data deposition, processing and retrieval of maps and fitted models.  ... 
doi:10.1016/s0076-6879(10)83004-6 pmid:20888470 pmcid:PMC2966391 fatcat:ncsypzwkdvh6dopessk56ubpaq

EMDataBank unified data resource for 3DEM

Catherine L. Lawson, Ardan Patwardhan, Matthew L. Baker, Corey Hryc, Eduardo Sanz Garcia, Brian P. Hudson, Ingvar Lagerstedt, Steven J. Ludtke, Grigore Pintilie, Raul Sala, John D. Westbrook, Helen M. Berman (+2 others)
2015 Nucleic Acids Research  
The EMDataBank project provides a unified portal for deposition, retrieval and analysis of 3DEM density maps, atomic models and associated metadata (emdatabank.org).  ...  In addition, we describe progress and approaches toward development of validation protocols and methods, working with the scientific community, in order to create a validation pipeline for 3DEM data.  ...  EMDataBank Unified Data Resource for 3DEM is supported by the National Institutes of Health [R01GM079429] to Baylor College of Medicine, Rutgers University and the EMBL-European Bioinformatics Institute  ... 
doi:10.1093/nar/gkv1126 pmid:26578576 pmcid:PMC4702818 fatcat:6dzeejw3njcztaypxe7tvqkglq

Databases and Archiving for CryoEM [chapter]

A. Patwardhan, C.L. Lawson
2016 Methods in Enzymology  
In this chapter we describe the current state of the archives, resources available for depositing, accessing, searching, visualising and validating data, on-going community-wide initiatives and opportunities  ...  and bioinformatics resources.  ...  EMDataBank Unified Data Resource is funded by National Institutes of Health GM079429 to Baylor College of Medicine (Wah Chiu, PI), Rutgers University (Helen Berman, co-PI), and EMBL-EBI (Gerard Kleywegt  ... 
doi:10.1016/bs.mie.2016.04.015 pmid:27572735 pmcid:PMC5351295 fatcat:kwqh4wmdhzb5rily4f6i2y53x4

VRmol: an Integrative Cloud-Based Virtual Reality System to Explore Macromolecular Structure [article]

Kui Xu, Nan Liu, Jingle Xu, Chunlong Guo, Lingyun Zhao, Hong-Wei Wang, Qiangfeng Cliff Zhang
2019 bioRxiv   pre-print
ABSTRACTPast decades have seen much effort devoted to the tool development for biomacromolecule structural visualization and analysis.  ...  We thank Haitao Li (Tsinghua University) for helpful comments on the development of VRmol. We also thank Maoxiang Shi for useful suggestions to improve the efficiency of VRmol.  ...  Lawson, C.L., et al., EMDataBank.org: unified data resource for CryoEM. Nucleic Acids Res, 2011. 39(Database issue): p. D456-64. 34.  ... 
doi:10.1101/589366 fatcat:qjmglmp6qzfkhfk6folfesxedy

Advances in Electron Microscopy with Deep Learning

Jeffrey Ede
2020 Zenodo  
and automatic data clustering by t-distributed stochastic neighbour embedding; adaptive learning rate clipping to stabilize learning; generative adversarial networks for compressed sensing with spiral  ...  in Physics will be typeset for physical printing and binding.  ...  Acknowledgements Thanks go to Jeremy Sloan and Martin Lotz for internally reviewing this article.  ... 
doi:10.5281/zenodo.4399748 fatcat:63ggmnviczg6vlnqugbnrexsgy

Advances in Electron Microscopy with Deep Learning

Jeffrey Ede
2020 Zenodo  
and automatic data clustering by t-distributed stochastic neighbour embedding; adaptive learning rate clipping to stabilize learning; generative adversarial networks for compressed sensing with spiral  ...  Philosophy in Physics is typeset for physical printing and binding.  ...  Acknowledgements Thanks go to Jeremy Sloan and Martin Lotz for internally reviewing this article.  ... 
doi:10.5281/zenodo.4591029 fatcat:zn2hvfyupvdwlnvsscdgswayci

Advances in Electron Microscopy with Deep Learning

Jeffrey Ede
2020 Zenodo  
and automatic data clustering by t-distributed stochastic neighbour embedding; adaptive learning rate clipping to stabilize learning; generative adversarial networks for compressed sensing with spiral  ...  Philosophy in Physics is typeset for physical printing and binding.  ...  Acknowledgements Thanks go to Jeremy Sloan and Martin Lotz for internally reviewing this article.  ... 
doi:10.5281/zenodo.4598227 fatcat:hm2ksetmsvf37adjjefmmbakvq

Advances in Electron Microscopy with Deep Learning

Jeffrey Ede
2020 Zenodo  
and automatic data clustering by t-distributed stochastic neighbour embedding; adaptive learning rate clipping to stabilize learning; generative adversarial networks for compressed sensing with spiral  ...  in Physics will be typeset for physical printing and binding.  ...  Acknowledgements Thanks go to Jeremy Sloan and Martin Lotz for internally reviewing this article.  ... 
doi:10.5281/zenodo.4413249 fatcat:35qbhenysfhvza2roihx52afuy

Advances in Electron Microscopy with Deep Learning

Jeffrey Ede
2020 Zenodo  
and automatic data clustering by t-distributed stochastic neighbour embedding; adaptive learning rate clipping to stabilize learning; generative adversarial networks for compressed sensing with spiral  ...  in Physics will be typeset for physical printing and binding.  ...  Acknowledgements Thanks go to Jeremy Sloan and Martin Lotz for internally reviewing this article.  ... 
doi:10.5281/zenodo.4415407 fatcat:6dejwzzpmfegnfuktrld6zgpiq

Advances in Electron Microscopy with Deep Learning

Jeffrey Ede
2020 Zenodo  
and automatic data clustering by t-distributed stochastic neighbour embedding; adaptive learning rate clipping to stabilize learning; generative adversarial networks for compressed sensing with spiral  ...  in Physics will be typeset for physical printing and binding.  ...  Acknowledgements Thanks go to Jeremy Sloan and Martin Lotz for internally reviewing this article.  ... 
doi:10.5281/zenodo.4429792 fatcat:qs6yuapx4vdbdmwna7ix7nnwty