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Protein Design
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Formally, given the design requirements of users, models are required to generate protein amino acid sequences that align with those requirements.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Geometric deep learning assists protein engineering. Opportunities and Challenges
Natural Language Guided Ligand-Binding Protein Design
AlphaFold Database Debiasing for Robust Inverse Folding
Protriever: End-to-End Differentiable Protein Homology Search for Fitness Prediction
ProteinZero: Self-Improving Protein Generation via Online Reinforcement Learning
Improving large language models with concept-aware fine-tuning
Diffusion Sequence Models for Enhanced Protein Representation and Generation
Improving Protein Sequence Design through Designability Preference Optimization
CFP-Gen: Combinatorial Functional Protein Generation via Diffusion Language Models
Breaking the Performance Ceiling in Complex Reinforcement Learning requires Inference Strategies
Protein Design with Dynamic Protein Vocabulary
PDFBench: A Benchmark for De novo Protein Design from Function
DS-ProGen: A Dual-Structure Deep Language Model for Functional Protein Design
PSBench: a large-scale benchmark for estimating the accuracy of protein complex structural models
Scoring-Assisted Generative Exploration for Proteins (SAGE-Prot): A Framework for Multi-Objective Protein Optimization via Iterative Sequence Generation and Evaluation
ProT-GFDM: A Generative Fractional Diffusion Model for Protein Generation
Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles
The Dance of Atoms-De Novo Protein Design with Diffusion Model
ProtFlow: Fast Protein Sequence Design via Flow Matching on Compressed Protein Language Model Embeddings
Prot42: a Novel Family of Protein Language Models for Target-aware Protein Binder Generation
Multi-Objective Quality-Diversity in Unstructured and Unbounded Spaces
Advanced Deep Learning Methods for Protein Structure Prediction and Design
ProtTeX: Structure-In-Context Reasoning and Editing of Proteins with Large Language Models
Proteina: Scaling Flow-based Protein Structure Generative Models
Applying computational protein design to therapeutic antibody discovery -- current state and perspectives
A Model-Centric Review of Deep Learning for Protein Design
ReQFlow: Rectified Quaternion Flow for Efficient and High-Quality Protein Backbone Generation
MotifBench: A standardized protein design benchmark for motif-scaffolding problems
Agentic End-to-End De Novo Protein Design for Tailored Dynamics Using a Language Diffusion Model
Persistent Sheaf Laplacian Analysis of Protein Flexibility
Steering Protein Family Design through Profile Bayesian Flow
Fast and Accurate Antibody Sequence Design via Structure Retrieval
Iterative Importance Fine-tuning of Diffusion Models
A Variational Perspective on Generative Protein Fitness Optimization
Controllable Protein Sequence Generation with LLM Preference Optimization
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