SOTAVerified

Protein Design

Formally, given the design requirements of users, models are required to generate protein amino acid sequences that align with those requirements.

Papers

Showing 161170 of 175 papers

TitleStatusHype
Robust Model-Based Optimization for Challenging Fitness LandscapesCode0
Scoring-Assisted Generative Exploration for Proteins (SAGE-Prot): A Framework for Multi-Objective Protein Optimization via Iterative Sequence Generation and EvaluationCode0
Generative Models for Graph-Based Protein DesignCode0
Building Confidence in Deep Generative Protein DesignCode0
Generative Adversarial Model-Based Optimization via Source Critic RegularizationCode0
Unsupervisedly Prompting AlphaFold2 for Few-Shot Learning of Accurate Folding Landscape and Protein Structure PredictionCode0
Fast and Flexible Protein Design Using Deep Graph Neural NetworksCode0
Inference-Time Alignment in Diffusion Models with Reward-Guided Generation: Tutorial and ReviewCode0
Gate-based Quantum Computing for Protein DesignCode0
Variational auto-encoding of protein sequencesCode0
Show:102550
← PrevPage 17 of 18Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GraphTransPerplexity6.63Unverified
2StructGNNPerplexity6.4Unverified
3AlphaDesignPerplexity6.3Unverified
4GCAPerplexity6.05Unverified
5GVPPerplexity5.36Unverified
6ProteinMPNNPerplexity4.61Unverified
7PiFoldPerplexity4.55Unverified
8Knowledge-DesignPerplexity3.46Unverified
#ModelMetricClaimedVerifiedStatus
1ESM-IFPerplexity6.44Unverified
2GVP-largePerplexity6.17Unverified