An Advanced Computational Tool for Local Quality Estimation of Protein Models from EM Maps Using Deep Learning
An Advanced Deep Learning Tool for Identifying Protein Secondary Structures and Nucleic Acids in Medium-to-Low Resolution EM Maps.
An Advanced Deep Learning Tool for Accurately Identifying Protein Secondary Structures in Medium-to-Low Resolution EM Maps.
A Tool for Directly Segmenting Individual Components from EM Maps Using Symmetry Restraints and Minimum Spanning Trees.
A Computational Tool for More Effective Protein Structure Information Capture Using Deep Learning.
A Database of Precomputed Residue-Wise Local Quality Scores for Protein Models from Cryo-EM Maps.
A web-based tool for real-time comparison and analysis of EM density maps.
A modeling tool that builds protein 3D models from EM maps using deep learning and can assign chain identity to homo-multimers.
An Advanced Computational Tool for Automatic Building of Full DNA/RNA Atomic Structures from Cryo-EM Maps Using Deep Learning.
A Model Refinement tool for Low-quality Regions in a protein structure model by DAQ score and AlphaFold2.
A Modeling Tool that directly traces main-chain connections and C-alpha positions by using Tree-Graph models.
Map-map fitting Tool for Accurate Superimposition of EM Maps Using Mean Shift Algorithm and FFT.
cryo-READ, Emap2sec+, DeepMainmast, VESPER are available on kiharalab server.
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