Protein Folding
38 papers with code • 0 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Protein Folding
PS4
Most implemented papers
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
The last decade has witnessed an experimental revolution in data science and machine learning, epitomised by deep learning methods.
Highly accurate protein structure prediction with AlphaFold
deepmind/alphafold
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Nature 2021
Accurate computational approaches are needed to address this gap and to enable large-scale structural bioinformatics.
Rethinking Neural Operations for Diverse Tasks
mkhodak/relax
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NeurIPS 2021
An important goal of AutoML is to automate-away the design of neural networks on new tasks in under-explored domains.
Variational Encoding of Complex Dynamics
msmbuilder/vde
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Recent work in the field of deep learning has led to the development of variational autoencoders (VAE), which are able to compress complex datasets into simpler manifolds.
TorchMD: A deep learning framework for molecular simulations
torchmd/torchmd
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Molecular dynamics simulations provide a mechanistic description of molecules by relying on empirical potentials.
ParaFold: Paralleling AlphaFold for Large-Scale Predictions
We evaluated the accuracy and efficiency of optimizations on CPUs and GPUs, and showed the large-scale prediction capability by running ParaFold inferences of 19, 704 small proteins in five hours on one NVIDIA DGX-2.
Enhancing the Protein Tertiary Structure Prediction by Multiple Sequence Alignment Generation
magiccircuit/msa-augmentor
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The field of protein folding research has been greatly advanced by deep learning methods, with AlphaFold2 (AF2) demonstrating exceptional performance and atomic-level precision.
A Parallel Trajectory Swapping Wang - Landau Study Of The HP Protein Model
The native results for the benchmark sequences and lattice polymers were compared with varying computational methods.
Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model
Using our predicted contacts as restraints, we can (ab initio) fold 208 of the 398 membrane proteins with TMscore>0. 5.
Simultaneous Coherent Structure Coloring facilitates interpretable clustering of scientific data by amplifying dissimilarity
sCSC performs a sequence of binary splittings on the dataset such that the most dissimilar data points are required to be in separate clusters.
