SOTAVerified

Protein Structure Prediction

Papers

Showing 150 of 188 papers

TitleStatusHype
Galactica: A Large Language Model for ScienceCode4
OpenProteinSet: Training data for structural biology at scaleCode4
Highly accurate protein structure prediction with AlphaFoldCode3
Robust deep learning based protein sequence design using ProteinMPNNCode3
MotifBench: A standardized protein design benchmark for motif-scaffolding problemsCode2
FastFold: Reducing AlphaFold Training Time from 11 Days to 67 HoursCode2
Protein Large Language Models: A Comprehensive SurveyCode2
MegaFold: System-Level Optimizations for Accelerating Protein Structure Prediction ModelsCode2
State-specific protein-ligand complex structure prediction with a multi-scale deep generative modelCode2
SE(3) diffusion model with application to protein backbone generationCode2
Protein structure generation via folding diffusionCode2
Distribution-Free, Risk-Controlling Prediction SetsCode2
Training on test proteins improves fitness, structure, and function predictionCode2
PyMOLfold: Interactive Protein and Ligand Structure Prediction in PyMOLCode2
ProteinBERT: a universal deep-learning model of protein sequence and functionCode2
Pareto Dominance Archive and Coordinated Selection Strategy-Based Many-Objective Optimizer for Protein Structure PredictionCode1
MSAGPT: Neural Prompting Protein Structure Prediction via MSA Generative Pre-TrainingCode1
A Graph Neural Network Approach to Automated Model Building in Cryo-EM MapsCode1
Towards Interpretable Protein Structure Prediction with Sparse AutoencodersCode1
Accurate Protein Structure Prediction by Embeddings and Deep Learning RepresentationsCode1
Iterative SE(3)-TransformersCode1
RDesign: Hierarchical Data-efficient Representation Learning for Tertiary Structure-based RNA DesignCode1
ProteinNet: a standardized data set for machine learning of protein structureCode1
PEER: A Comprehensive and Multi-Task Benchmark for Protein Sequence UnderstandingCode1
CREMP: Conformer-rotamer ensembles of macrocyclic peptides for machine learningCode1
SidechainNet: An All-Atom Protein Structure Dataset for Machine LearningCode1
Accurate and efficient protein embedding using multi-teacher distillation learningCode1
Generative diffusion model with inverse renormalization group flowsCode1
A Hitchhiker's Guide to Geometric GNNs for 3D Atomic SystemsCode1
Generating Novel, Designable, and Diverse Protein Structures by Equivariantly Diffusing Oriented Residue CloudsCode1
Protein Language Models and Structure Prediction: Connection and ProgressionCode1
Highly accurate and efficient deep learning paradigm for full-atom protein loop modeling with KarmaLoopCode1
Energy-based models for atomic-resolution protein conformationsCode1
EigenFold: Generative Protein Structure Prediction with Diffusion ModelsCode1
Enhancing the Protein Tertiary Structure Prediction by Multiple Sequence Alignment GenerationCode1
PolyFold: an interactive visual simulator for distance-based protein foldingCode1
ExplainableFold: Understanding AlphaFold Prediction with Explainable AICode1
DiffPack: A Torsional Diffusion Model for Autoregressive Protein Side-Chain PackingCode1
Deep Learning of Proteins with Local and Global Regions of DisorderCode1
AtomSurf : Surface Representation for Learning on Protein StructuresCode1
Conformation-Aware Structure Prediction of Antigen-Recognizing Immune ProteinsCode1
Generative De Novo Protein Design with Global ContextCode1
DeepProtein: Deep Learning Library and Benchmark for Protein Sequence LearningCode1
FoldMark: Protecting Protein Generative Models with WatermarkingCode1
Geometry-Complete Perceptron Networks for 3D Molecular GraphsCode1
MUST-CNN: A Multilayer Shift-and-Stitch Deep Convolutional Architecture for Sequence-based Protein Structure PredictionCode0
Applying Deep Reinforcement Learning to the HP Model for Protein Structure PredictionCode0
PDB-Struct: A Comprehensive Benchmark for Structure-based Protein DesignCode0
MAS2HP: A Multi Agent System to Predict Protein Structure in 2D HP modelCode0
APACE: AlphaFold2 and advanced computing as a service for accelerated discovery in biophysicsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GAL 125MValidation perplexity20.62Unverified
2GAL 1.3BValidation perplexity17.58Unverified
3GAL 6.7BValidation perplexity17.29Unverified
4GAL 30BValidation perplexity17.27Unverified
5GAL 120BValidation perplexity17.26Unverified
#ModelMetricClaimedVerifiedStatus
1GAL 125MValidation perplexity19.18Unverified
2GAL 1.3BValidation perplexity17.04Unverified
3GAL 6.7BValidation perplexity16.35Unverified
4GAL 30BValidation perplexity15.42Unverified
5GAL 120BValidation perplexity12.77Unverified
#ModelMetricClaimedVerifiedStatus
1GAL 125MValidation perplexity16.35Unverified
2GAL 1.3BValidation perplexity12.53Unverified
3GAL 6.7BValidation perplexity7.76Unverified
4GAL 30BValidation perplexity4.28Unverified
5GAL 120BValidation perplexity3.14Unverified
#ModelMetricClaimedVerifiedStatus
1GAL 125MValidation perplexity19.05Unverified
2GAL 1.3BValidation perplexity15.82Unverified
3GAL 6.7BValidation perplexity11.58Unverified
4GAL 30BValidation perplexity8.23Unverified
5GAL 120BValidation perplexity5.54Unverified