Papers Protein Function Prediction
“Protein Function Prediction” 태그가 달린 논문 89편 · 필터 해제
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 GenerationBioBlobs: Unsupervised Discovery of Functional Substructures for Protein Function Prediction
Protein function is driven by cohesive substructures, such as catalytic triads, binding pockets, and structural motifs, that occupy only a small fraction of a protein's residues. Yet existing pipelines built on protein e…
Protein Function PredictionSparse Autoencoders for Low-$N$ Protein Function Prediction and Design
Predicting protein function from amino acid sequence remains a central challenge in data-scarce (low-$N$) regimes, limiting machine learning-guided protein design when only small amounts of assay-labeled sequence-functio…
Protein Function PredictionProtein DesignProtTeX-CC: Activating In-Context Learning in Protein LLM via Two-Stage Instruction Compression
Recent advances in protein large language models, such as ProtTeX, represent both side-chain amino acids and backbone structure as discrete token sequences of residue length. While this design enables unified modeling of…
Protein Function PredictionUnderstanding protein function with a multimodal retrieval-augmented foundation model
Protein language models (PLMs) learn probability distributions over natural protein sequences. By learning from hundreds of millions of natural protein sequences, protein understanding and design capabilities emerge. Rec…
Protein Function PredictionRepresentation LearningAnnoDPO: Protein Functional Annotation Learning with Direct Preference Optimization
Deciphering protein function remains a fundamental challenge in protein representation learning. The task presents significant difficulties for protein language models (PLMs) due to the sheer volume of functional annotat…
Language ModelingLanguage ModellingLarge Language ModelProtein Function Prediction+1Into the Unknown: From Structure to Disorder in Protein Function Prediction
Intrinsically disordered regions (IDRs) account for one-third of the human proteome and play essential biological roles. However, predicting the functions of IDRs remains a major challenge due to their lack of stable str…
Models AlignmentProtein Function PredictionSTELLA: Towards Protein Function Prediction with Multimodal LLMs Integrating Sequence-Structure Representations
Protein biology focuses on the intricate relationships among sequences, structures, and functions. Deciphering protein functions is crucial for understanding biological processes, advancing drug discovery, and enabling s…
Drug DiscoveryGeneral KnowledgePredictionProtein Function PredictionMSNGO: multi-species protein function annotation based on 3D protein structure and network propagation
Motivation: In recent years, protein function prediction has broken through the bottleneck of sequence features, significantly improving prediction accuracy using high-precision protein structures predicted by AlphaFold2…
Graph Representation LearningPredictionProtein Function PredictionRepresentation LearningProtTeX: Structure-In-Context Reasoning and Editing of Proteins with Large Language Models
Large language models have made remarkable progress in the field of molecular science, particularly in understanding and generating functional small molecules. This success is largely attributed to the effectiveness of m…
multimodal generationProtein DesignProtein Function PredictionevoBPE: Evolutionary Protein Sequence Tokenization
Recent advancements in computational biology have drawn compelling parallels between protein sequences and linguistic structures, highlighting the need for sophisticated tokenization methods that capture the intricate ev…
Protein Function PredictionComputational Protein Science in the Era of Large Language Models (LLMs)
Considering the significance of proteins, computational protein science has always been a critical scientific field, dedicated to revealing knowledge and developing applications within the protein sequence-structure-func…
Drug DiscoveryProtein DesignProtein Function PredictionProtein Structure PredictionGoBERT: Gene Ontology Graph Informed BERT for Universal Gene Function Prediction
Exploring the functions of genes and gene products is crucial to a wide range of fields, including medical research, evolutionary biology, and environmental science. However, discovering new functions largely relies on e…
Implicit RelationsMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATIONPrediction+1ProtCLIP: Function-Informed Protein Multi-Modal Learning
Multi-modality pre-training paradigm that aligns protein sequences and biological descriptions has learned general protein representations and achieved promising performance in various downstream applications. However, t…
Protein Function PredictionSemantic SimilaritySemantic Textual SimilarityProtBoost: protein function prediction with Py-Boost and Graph Neural Networks -- CAFA5 top2 solution
Predicting protein properties, functions and localizations are important tasks in bioinformatics. Recent progress in machine learning offers an opportunities for improving existing methods. We developed a new approach ca…
Protein Function Prediction