This dataset contains protein 3D models that can be used to train a machine learning or deep learning method for protein model refinement and model quality assessment. Meanwhile, Data4GNNRefine-part1.tar.gz includes the protein 3D models built by RaptorX for more than 25000 CathS35 proteins. Both the template-free and template-based methods are used to build these 3D models. Data4GNNRefine-part2.tar.gz includes the protein models released by CASPs and CAMEO. This file also contains the native structures of the protein models
Summary: The reliable assessment of the quality of protein struc-tural models is fundamental to the ...
Recently, predicting proteins three-dimensional (3D) structure from its sequence information has mad...
We present a new knowledge-based Model Quality Assessment Program (MQAP) at the residue level which ...
Once you have generated a 3D model of a protein, how do you know whether it bears any resemblance to...
International audienceProtein model quality assessment (QA) is a crucial and yet open problem in str...
Raw + Processed Datasets used in the ProteinWorkshop Representation Learning Benchmark Includes ...
Many protein structure prediction programs exist and they can efficiently generate a number of prote...
Motivation: Modelling the 3D structures of proteins can often be enhanced if more than one fold temp...
In protein tertiary structure prediction, model quality assessment programs (MQAPs) are often used t...
Model quality assessment programs (MQAPs) aim to assess the quality of modelled 3D protein structure...
This data contains two sets of deep ResNet models for RaptorX-3DModeling. One set of models is used ...
The refinement of predicted 3D protein models is crucial in bringing them closer towards experimenta...
The reliable assessment of the quality of protein structural models is fundamental to the progress o...
Abstract Background Protein structure prediction has achieved a lot of progress during the last few ...
Abstract Background Experimental determination of protein 3D structures is expensive, time consuming...
Summary: The reliable assessment of the quality of protein struc-tural models is fundamental to the ...
Recently, predicting proteins three-dimensional (3D) structure from its sequence information has mad...
We present a new knowledge-based Model Quality Assessment Program (MQAP) at the residue level which ...
Once you have generated a 3D model of a protein, how do you know whether it bears any resemblance to...
International audienceProtein model quality assessment (QA) is a crucial and yet open problem in str...
Raw + Processed Datasets used in the ProteinWorkshop Representation Learning Benchmark Includes ...
Many protein structure prediction programs exist and they can efficiently generate a number of prote...
Motivation: Modelling the 3D structures of proteins can often be enhanced if more than one fold temp...
In protein tertiary structure prediction, model quality assessment programs (MQAPs) are often used t...
Model quality assessment programs (MQAPs) aim to assess the quality of modelled 3D protein structure...
This data contains two sets of deep ResNet models for RaptorX-3DModeling. One set of models is used ...
The refinement of predicted 3D protein models is crucial in bringing them closer towards experimenta...
The reliable assessment of the quality of protein structural models is fundamental to the progress o...
Abstract Background Protein structure prediction has achieved a lot of progress during the last few ...
Abstract Background Experimental determination of protein 3D structures is expensive, time consuming...
Summary: The reliable assessment of the quality of protein struc-tural models is fundamental to the ...
Recently, predicting proteins three-dimensional (3D) structure from its sequence information has mad...
We present a new knowledge-based Model Quality Assessment Program (MQAP) at the residue level which ...