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Protein Language Model
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Use of protein language models in protein property prediction
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Protein Design with Dynamic Protein Vocabulary
Structure-Aligned Protein Language Model
Leveraging Protein Language Model Embeddings for Catalytic Turnover Prediction of Adenylate Kinase Orthologs in a Low-Data Regime
ProtFlow: Fast Protein Sequence Design via Flow Matching on Compressed Protein Language Model Embeddings
Customizing Spider Silk: Generative Models with Mechanical Property Conditioning for Protein Engineering
Chem42: a Family of chemical Language Models for Target-aware Ligand Generation
ExPath: Towards Explaining Targeted Pathways for Biological Knowledge Bases
InfoBridge: Mutual Information estimation via Bridge Matching
Learning to engineer protein flexibility
Pre-trained protein language model for codon optimization
Multi-Scale Representation Learning for Protein Fitness Prediction
DapPep: Domain Adaptive Peptide-agnostic Learning for Universal T-cell Receptor-antigen Binding Affinity Prediction
High fitness paths can connect proteins with low sequence overlap
Long-context Protein Language Modeling Using Bidirectional Mamba with Shared Projection Layers
Retrieval-Enhanced Mutation Mastery: Augmenting Zero-Shot Prediction of Protein Language Model
Peptide-GPT: Generative Design of Peptides using Generative Pre-trained Transformers and Bio-informatic Supervision
DPLM-2: A Multimodal Diffusion Protein Language Model
Fine-tuning the ESM2 protein language model to understand the functional impact of missense variants
Approximating mutual information of high-dimensional variables using learned representations
Peptide Sequencing Via Protein Language Models
tcrLM: a lightweight protein language model for predicting T cell receptor and epitope binding specificity
Robust Optimization in Protein Fitness Landscapes Using Reinforcement Learning in Latent Space
AntiFold: Improved antibody structure-based design using inverse folding
Beyond ESM2: Graph-Enhanced Protein Sequence Modeling with Efficient Clustering
Detection of circular permutations by Protein Language Models
AMPCliff: quantitative definition and benchmarking of activity cliffs in antimicrobial peptides
DisorderUnetLM: Validating ProteinUnet for efficient protein intrinsic disorder prediction
On Recovering Higher-order Interactions from Protein Language Models
Application of Quantum Tensor Networks for Protein Classification
Diffusion on language model encodings for protein sequence generation
ESM All-Atom: Multi-scale Protein Language Model for Unified Molecular Modeling
A Protein Structure Prediction Approach Leveraging Transformer and CNN Integration
Diffusion Language Models Are Versatile Protein Learners
ProtIR: Iterative Refinement between Retrievers and Predictors for Protein Function Annotation
Decoupled Sequence and Structure Generation for Realistic Antibody Design
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