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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.
{"references": ["https://www.biorxiv.org/content/10.1101/2020.12.10.419994v1"]}
protein structure prediction, machine learning, deep learning, protein model quality assessment, protein model refinement
protein structure prediction, machine learning, deep learning, protein model quality assessment, protein model refinement
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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