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Protein Folding

Papers

Showing 101–125 of 185 papers

TitleStatusHype
First-passage times in complex energy landscapes: a case study with nonmuscle myosin II assembly—0
A 23 MW data centre is all you need—0
Disentangled Spatiotemporal Graph Generative Models—0
From evolution to folding of repeat proteins—0
Collective Variable for Metadynamics Derived from AlphaFold Output—0
Prompt-Guided Injection of Conformation to Pre-trained Protein Model—0
DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for AI-aided Drug Discovery -- A Focus on Affinity Prediction Problems with Noise AnnotationsCode0
GraphVAMPNet, using graph neural networks and variational approach to markov processes for dynamical modeling of biomolecules—0
RoMA: a Method for Neural Network Robustness Measurement and Assessment—0
Protein Folding Neural Networks Are Not Robust—0
Variational embedding of protein folding simulations using gaussian mixture variational autoencoders—0
Exploring generative atomic models in cryo-EM reconstruction—0
Embedding Principle of Loss Landscape of Deep Neural Networks—0
Protein folding simulations in the hydrophobic-polar model using a hybrid cuckoo search algorithm—0
EBM-Fold: Fully-Differentiable Protein Folding Powered by Energy-based Models—0
Predictive landscapes hidden beneath biological cellular automata—0
Quadratic Optimization-Based Nonlinear Control for Protein Conformation Prediction—0
Coupling streaming AI and HPC ensembles to achieve 100-1000x faster biomolecular simulations—0
Mimetic Neural Networks: A unified framework for Protein Design and Folding—0
QFold: Quantum Walks and Deep Learning to Solve Protein FoldingCode0
Analyzing the Performance of Graph Neural Networks with Pipe Parallelism—0
Exact Reduction of Huge Action Spaces in General Reinforcement Learning—0
The finite size effects and the two-state paradigm of protein folding—0
Disentangled Dynamic Graph Deep GenerationCode0
The role of hydrophobic interactions in folding of β-sheets—0
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