Protein Function Prediction
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Benchmarks
Most implemented
Strategies for Pre-training Graph Neural Networks
A Systematic Study of Joint Representation Learning on Protein Sequences and Structures
ProtFAD: Introducing function-aware domains as implicit modality towards protein function prediction
Papers
Structural Interpretations of Protein Language Model Representations via Differentiable Graph Partitioning
Protein language models such as ESM-2 learn rich residue representations that achieve strong performance on protein function prediction, but their features remain difficult to interpret as structural $\&$ evolutionary si…
Protein Function PredictionProtein Language Modelgraph partitioningBetter Protein Function Prediction by Modeling Survivorship Bias
Protein sequence data from nature exhibits survivorship bias: we only observe data from those organisms that survive and reproduce, while non-functional protein mutations are eliminated by natural selection. Thus, predic…
Protein Function PredictionInterleaved Tool-Call Reasoning for Protein Function Understanding
Recent advances in large language models (LLMs) have highlighted the effectiveness of chain-of-thought reasoning in symbolic domains such as mathematics and programming. However, our study shows that directly transferrin…
Protein Function PredictionReinforcement LearningAnswer GenerationSTAR-GO: Improving Protein Function Prediction by Learning to Hierarchically Integrate Ontology-Informed Semantic Embeddings
Accurate prediction of protein function is essential for elucidating molecular mechanisms and advancing biological and therapeutic discovery. Yet experimental annotation lags far behind the rapid growth of protein sequen…
Protein Function PredictionZero-shot GeneralizationEnhancing Multimodal Protein Function Prediction Through Dual-Branch Dynamic Selection with Reconstructive Pre-Training
Multimodal protein features play a crucial role in protein function prediction. However, these features encompass a wide range of information, ranging from structural data and sequence features to protein attributes and …
Hierarchical Multi-label ClassificationProtein Function PredictionA Novel Framework for Multi-Modal Protein Representation Learning
Accurate protein function prediction requires integrating heterogeneous intrinsic signals (e.g., sequence and structure) with noisy extrinsic contexts (e.g., protein-protein interactions and GO term annotations). However…
Protein Function PredictionRepresentation LearningGraph Generation