Haruspex: A Neural Network for the Automatic Identification of Oligonucleotides and Protein Secondary Structure in Cryo‐Electron Microscopy Maps
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Title
Haruspex: A Neural Network for the Automatic Identification of Oligonucleotides and Protein Secondary Structure in Cryo‐Electron Microscopy Maps
Authors
Keywords
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Journal
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION
Volume -, Issue -, Pages -
Publisher
Wiley
Online
2020-03-19
DOI
10.1002/anie.202000421
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Note: Only part of the references are listed.- Deep Learning to Predict Protein Backbone Structure from High-Resolution Cryo-EM Density Maps
- (2020) Dong Si et al. Scientific Reports
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- (2019) Peter B. Rosenthal IUCrJ
- Protein secondary structure detection in intermediate-resolution cryo-EM maps using deep learning
- (2019) Sai Raghavendra Maddhuri Venkata Subramaniya et al. NATURE METHODS
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- (2018) Madhumati Sevvana et al. STRUCTURE
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- (2018) Genki Terashi et al. Nature Communications
- Current approaches for the fitting and refinement of atomic models into cryo-EM maps using CCP-EM
- (2018) Robert A. Nicholls et al. Acta Crystallographica Section D-Structural Biology
- New tools for the analysis and validation of cryo-EM maps and atomic models
- (2018) Pavel V. Afonine et al. Acta Crystallographica Section D-Structural Biology
- U-Net: deep learning for cell counting, detection, and morphometry
- (2018) Thorsten Falk et al. NATURE METHODS
- A fully automatic method yielding initial models from high-resolution cryo-electron microscopy maps
- (2018) Thomas C. Terwilliger et al. NATURE METHODS
- New tools for automated high-resolution cryo-EM structure determination in RELION-3
- (2018) Jasenko Zivanov et al. eLife
- Fully Convolutional Networks for Semantic Segmentation
- (2017) Evan Shelhamer et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- RosettaES: a sampling strategy enabling automated interpretation of difficult cryo-EM maps
- (2017) Brandon Frenz et al. NATURE METHODS
- Recent developments in the CCP-EM software suite
- (2017) Tom Burnley et al. Acta Crystallographica Section D-Structural Biology
- Visual automated macromolecular model building
- (2013) Gerrit G. Langer et al. ACTA CRYSTALLOGRAPHICA SECTION D-BIOLOGICAL CRYSTALLOGRAPHY
- A Machine Learning Approach for the Identification of Protein Secondary Structure Elements from Electron Cryo-Microscopy Density Maps
- (2012) Dong Si et al. BIOPOLYMERS
- Using a conformation-dependent stereochemical library improves crystallographic refinement of proteins
- (2010) Dale E. Tronrud et al. ACTA CRYSTALLOGRAPHICA SECTION D-BIOLOGICAL CRYSTALLOGRAPHY
- Features and development ofCoot
- (2010) P. Emsley et al. ACTA CRYSTALLOGRAPHICA SECTION D-BIOLOGICAL CRYSTALLOGRAPHY
- MolProbity: all-atom structure validation for macromolecular crystallography
- (2009) Vincent B. Chen et al. ACTA CRYSTALLOGRAPHICA SECTION D-BIOLOGICAL CRYSTALLOGRAPHY
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