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Literature DB >> 31192591

Frontiers in CryoEM Modeling.

Giulia Palermo¹, Yuji Sugita^2,3,4, Willy Wriggers⁵, Rommie E Amaro⁶.

Abstract

Entities: Disease Gene Species

Mesh：

Year: 2019 PMID： 31192591 PMCID： PMC6646052 DOI： 10.1021/acs.jcim.9b00412

Source DB: PubMed Journal: J Chem Inf Model ISSN： 1549-9596 Impact factor: 4.956

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21 in total

1. Normal mode based flexible fitting of high-resolution structure into low-resolution experimental data from cryo-EM.

Authors: Florence Tama; Osamu Miyashita; Charles L Brooks
Journal: J Struct Biol Date: 2004-09 Impact factor: 2.867

2. Protein structure fitting and refinement guided by cryo-EM density.

Authors: Maya Topf; Keren Lasker; Ben Webb; Haim Wolfson; Wah Chiu; Andrej Sali
Journal: Structure Date: 2008-02 Impact factor: 5.006

3. Flexible fitting of atomic structures into electron microscopy maps using molecular dynamics.

Authors: Leonardo G Trabuco; Elizabeth Villa; Kakoli Mitra; Joachim Frank; Klaus Schulten
Journal: Structure Date: 2008-05 Impact factor: 5.006

4. Trajectories of the ribosome as a Brownian nanomachine.

Authors: Ali Dashti; Peter Schwander; Robert Langlois; Russell Fung; Wen Li; Ahmad Hosseinizadeh; Hstau Y Liao; Jesper Pallesen; Gyanesh Sharma; Vera A Stupina; Anne E Simon; Jonathan D Dinman; Joachim Frank; Abbas Ourmazd
Journal: Proc Natl Acad Sci U S A Date: 2014-11-24 Impact factor: 11.205

5. Machine learning. Clustering by fast search and find of density peaks.

Authors: Alex Rodriguez; Alessandro Laio
Journal: Science Date: 2014-06-27 Impact factor: 47.728

6. Iterative elastic 3D-to-2D alignment method using normal modes for studying structural dynamics of large macromolecular complexes.

Authors: Qiyu Jin; Carlos Oscar S Sorzano; José Miguel de la Rosa-Trevín; José Román Bilbao-Castro; Rafael Núñez-Ramírez; Oscar Llorca; Florence Tama; Slavica Jonić
Journal: Structure Date: 2014-02-06 Impact factor: 5.006

Frontiers in CryoEM Modeling.

1. Normal mode based flexible fitting of high-resolution structure into low-resolution experimental data from cryo-EM.

2. Protein structure fitting and refinement guided by cryo-EM density.

3. Flexible fitting of atomic structures into electron microscopy maps using molecular dynamics.

4. Trajectories of the ribosome as a Brownian nanomachine.

5. Machine learning. Clustering by fast search and find of density peaks.

6. Iterative elastic 3D-to-2D alignment method using normal modes for studying structural dynamics of large macromolecular complexes.

7. The development of cryo-EM into a mainstream structural biology technique.

8. Atomic-accuracy models from 4.5-Å cryo-electron microscopy data with density-guided iterative local refinement.

9. ATTRACT-EM: a new method for the computational assembly of large molecular machines using cryo-EM maps.

10. Continuous changes in structure mapped by manifold embedding of single-particle data in cryo-EM.

1. Faces of Contemporary CryoEM Information and Modeling.