Protein Language Model
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Benchmarks
DAVIS-DTA
Most implemented
ESM-NBR: fast and accurate nucleic acid-binding residue prediction via protein language model feature representation and multi-task learning
Algorithm for Optimized mRNA Design Improves Stability and Immunogenicity
AbRank: A Benchmark Dataset and Metric-Learning Framework for Antibody-Antigen Affinity Ranking
Structure-Aligned Protein Language Model
Papers
Interpreting Protein Language Model Embeddings via Orthogonal Projection for Protein Fitness Prediction
Recently, there has been a growing adoption of protein language models (PLMs) in biomedical science. Their embeddings provide a rich numerical representation of protein sequences which achieve state-of-the-art performanc…
Protein Language ModelLC-SEPLM: long-range contact-supervised adaptation for sequence-only protein representation learning
Protein language models learn transferable sequence representations. However, because they primarily model contextual dependencies along amino-acid sequences, their training objectives do not explicitly constrain the mod…
Representation LearningProtein Language ModelStructure-Regularized Interpretable TCR-Epitope Prediction
T cell receptor (TCR)-epitope binding prediction is essential for understanding adaptive immunity and developing immunotherapies. Existing sequence- and structure-based models often generalize poorly to unseen epitopes a…
Protein Language Model3D Masked Autoencoders are Robust Learners of Volumetric and Multimodal Cellular Representations for Microscopy
Self-supervised learning in fluorescence microscopy often relies on 2D projections, despite the inherently three-dimensional nature of cells. We present a systematic comparison of 2D and 3D masked autoencoders (MAE-2D vs…
Self-Supervised LearningRepresentation LearningProtein Language ModelProtein-Based Fish Species Identification: Dataset, Models, and Insights from Native Bangladeshi Fish
Correct identification of fish species is highly significant for food security, economic development, and climate resilience in Bangladesh. Protein sequences directly reflect functional and evolutionary constraints which…
Protein Language ModelViral Proteins Reveal Geometry of Protein Language Models
Protein language models are trained on highly imbalanced datasets, raising the question of how they represent underrepresented biological sequences. Using viral proteins as a case study across ESM model families, we iden…
Protein Language Model