This data contains two sets of deep ResNet models for RaptorX-3DModeling. One set of models is used for the prediction of backbone phi, psi angles and the other set of models is used for the prediction of inter-atom distance and orientation probability distribution. The RaptorX-3DModeling package itself is available at https://github.com/j3xugit/RaptorX-3DModelin
With the debut of AlphaFold2, we now can get a highly-accurate view of a reasonable equilibrium tert...
Thesis (Ph.D.)--University of Washington, 2022Understanding the rules of protein structure folding h...
DeepMind presented notably accurate predictions at the recent 14th Critical Assessment of Structure ...
This data contains two sets of deep ResNet models for RaptorX-3DModeling. One set of models is used ...
This dataset contains two sets of deep ResNet models for RaptorX-3DModeling. One set of models is us...
This dataset contains the multiple sequence alignments (MSAs) and experimental structure files of th...
This dataset contains protein 3D models that can be used to train a machine learning or deep learnin...
Supplementary Material. This additional file contains two parts: S1. supplementary methods for vecto...
MotivationProtein structure prediction has been greatly improved by deep learning, but most efforts ...
The trRosetta structure prediction method employs deep learning to generate predicted residue-residu...
This additional file contains target list for the testing set from CASP12 consisting of 40 proteins....
This additional file contains target list for the testing set from PDB25 consisting of 1267 proteins...
This additional file contains target list for the validation set from PDB25 consisting of 1267 prote...
DeepMind presented notably accurate predictions at the recent 14th Critical Assessment of Structure ...
Protein structure prediction represents a significant challenge in the field of bioinformatics, with...
With the debut of AlphaFold2, we now can get a highly-accurate view of a reasonable equilibrium tert...
Thesis (Ph.D.)--University of Washington, 2022Understanding the rules of protein structure folding h...
DeepMind presented notably accurate predictions at the recent 14th Critical Assessment of Structure ...
This data contains two sets of deep ResNet models for RaptorX-3DModeling. One set of models is used ...
This dataset contains two sets of deep ResNet models for RaptorX-3DModeling. One set of models is us...
This dataset contains the multiple sequence alignments (MSAs) and experimental structure files of th...
This dataset contains protein 3D models that can be used to train a machine learning or deep learnin...
Supplementary Material. This additional file contains two parts: S1. supplementary methods for vecto...
MotivationProtein structure prediction has been greatly improved by deep learning, but most efforts ...
The trRosetta structure prediction method employs deep learning to generate predicted residue-residu...
This additional file contains target list for the testing set from CASP12 consisting of 40 proteins....
This additional file contains target list for the testing set from PDB25 consisting of 1267 proteins...
This additional file contains target list for the validation set from PDB25 consisting of 1267 prote...
DeepMind presented notably accurate predictions at the recent 14th Critical Assessment of Structure ...
Protein structure prediction represents a significant challenge in the field of bioinformatics, with...
With the debut of AlphaFold2, we now can get a highly-accurate view of a reasonable equilibrium tert...
Thesis (Ph.D.)--University of Washington, 2022Understanding the rules of protein structure folding h...
DeepMind presented notably accurate predictions at the recent 14th Critical Assessment of Structure ...
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