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Protein Structures with Incomplete and Inaccurate Distance Data
The dataset used in the paper is a set of protein structures with incomplete and inaccurate distance data. -
CASP dataset
The CASP dataset was used for testing. The dataset contains 96 template-free proteins and 90 template-based proteins. -
SCOP 2.06 dataset
The SCOP 2.06 dataset was used for testing. The dataset contains 4,188 domains, covering 550 folds. -
SCOP 1.75 dataset
The SCOP 1.75 dataset was used for training and validation. The dataset contains 16,712 proteins covering 7 major structural classes with total 1,195 identified folds. -
DeepSF: deep convolutional neural network for mapping protein sequences to folds
Protein fold recognition is an important problem in structural bioinformatics. Almost all traditional fold recognition methods use sequence (homology) comparison to indirectly... -
Protein-related datasets
The dataset used in the paper is a set of protein-related datasets. -
TORCHPROTEINLIBRARY
TORCHPROTEINLIBRARY is a library that implements the conversion between internal protein coordinates and atomic positions for “full-atom” and “backbone-only” models of protein... -
eBDIMS server
The eBDIMS server generates transition pathways between protein end-states, and allows for validation and rational analysis within the conformational landscape defined from... -
Amino acid sequences
Amino acid sequences used in experiments -
Two-phase protein folding optimization on a 3D AB off-lattice model
Two-phase optimization for protein folding optimization on a three-dimensional AB off-lattice model -
SGNet: Folding Symmetrical Protein Complex with Deep Learning
The SGNet dataset is a benchmark for symmetrical protein complex structure prediction. It contains a set of symmetrical protein complexes with different symmetry types (C, D, T,... -
Protein homology dataset
Protein homology dataset (KDD Cup 2004), with binary-valued features. -
BACKDIFF: A DIFFUSION MODEL FOR GENERALIZED TRANSFERABLE PROTEIN BACKMAPPING
Coarse-grained protein models play a crucial role in the study of protein structures, protein thermodynamic properties, and protein conformation dynamics. -
Impact of protein conformational diversity on alphafold predictions
Protein structure prediction has reached revolutionary levels of accuracy on single structures, yet distributional modeling paradigms are needed to capture the conformational... -
Fold-switching proteins and ligand-induced conformational change
Fold-switching proteins and ligand-induced conformational change. -
EIGENFOLD: Generative Protein Structure Prediction with Diffusion Models
Protein structure prediction has reached revolutionary levels of accuracy on single structures, yet distributional modeling paradigms are needed to capture the conformational...
