SOTAVerified

Protein Function Prediction

For GO terms prediction, given the specific function prediction instruction and a protein sequence, models characterize the protein functions using the GO terms presented in three different domains (cellular component, biological process, and molecular function).

Papers

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Showing 1–50 of 79 papers

TitleStatusHype
Galactica: A Large Language Model for ScienceCode4
Robust deep learning based protein sequence design using ProteinMPNNCode3
Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language ModelsCode2
A Systematic Study of Joint Representation Learning on Protein Sequences and StructuresCode2
Graph Self-supervised Learning with Accurate Discrepancy LearningCode1
MD-HIT: Machine learning for materials property prediction with dataset redundancy controlCode1
Coherent Hierarchical Multi-Label Classification NetworksCode1
Deep learning-based rapid generation of broadly reactive antibodies against SARS-CoV-2 and its Omicron variantCode1
Structure-Informed Protein Language ModelCode1
DeepProtein: Deep Learning Library and Benchmark for Protein Sequence LearningCode1
Multi-Scale Representation Learning on ProteinsCode1
OntoProtein: Protein Pretraining With Gene Ontology EmbeddingCode1
Strategies for Pre-training Graph Neural NetworksCode1
PEER: A Comprehensive and Multi-Task Benchmark for Protein Sequence UnderstandingCode1
Insights Into the Inner Workings of Transformer Models for Protein Function PredictionCode1
Endowing Protein Language Models with Structural KnowledgeCode1
Prot2Text: Multimodal Protein's Function Generation with GNNs and TransformersCode1
ProtBoost: protein function prediction with Py-Boost and Graph Neural Networks -- CAFA5 top2 solutionCode1
AnnoDPO: Protein Functional Annotation Learning with Direct Preference OptimizationCode0
AFDP: An Automated Function Description Prediction Approach to Improve Accuracy of Protein Function PredictionsCode0
Biomedical Knowledge Graph Embeddings with Negative StatementsCode0
Graph Embedding on Biomedical Networks: Methods, Applications, and EvaluationsCode0
Ankh: Optimized Protein Language Model Unlocks General-Purpose ModellingCode0
ProtFAD: Introducing function-aware domains as implicit modality towards protein function predictionCode0
evoBPE: Evolutionary Protein Sequence TokenizationCode0
Encoding protein dynamic information in graph representation for functional residue identificationCode0
EurNet: Efficient Multi-Range Relational Modeling of Spatial Multi-Relational DataCode0
Linear-scaling kernels for protein sequences and small molecules outperform deep learning while providing uncertainty quantitation and improved interpretabilityCode0
SCOP: A Sequence-Structure Contrast-Aware Framework for Protein Function PredictionCode0
MSNGO: multi-species protein function annotation based on 3D protein structure and network propagationCode0
Structure-Enhanced Meta-Learning For Few-Shot Graph ClassificationCode0
Multi-modal Representation Learning Enables Accurate Protein Function Prediction in Low-Data SettingCode0
Protein 3D Graph Structure Learning for Robust Structure-based Protein Property Prediction—0
ProteinEngine: Empower LLM with Domain Knowledge for Protein Engineering—0
Protein-Mamba: Biological Mamba Models for Protein Function Prediction—0
ProteinRPN: Towards Accurate Protein Function Prediction with Graph-Based Region Proposals—0
ProtNN: Fast and Accurate Nearest Neighbor Protein Function Prediction based on Graph Embedding in Structural and Topological Space—0
ProTranslator: zero-shot protein function prediction using textual description—0
ProtTeX: Structure-In-Context Reasoning and Editing of Proteins with Large Language Models—0
Random Embeddings and Linear Regression can Predict Protein Function—0
Regularization and Kernelization of the Maximin Correlation Approach—0
Reprogramming Pretrained Language Models for Protein Sequence Representation Learning—0
Self-supervised Learning and Graph Classification under Heterophily—0
SMISS: A protein function prediction server by integrating multiple sources—0
STELLA: Towards Protein Function Prediction with Multimodal LLMs Integrating Sequence-Structure Representations—0
Using Ontologies To Improve Performance In Massively Multi-label Prediction—0
A Vectorization Method Induced By Maximal Margin Classification For Persistent Diagrams—0
Using Ontologies To Improve Performance In Massively Multi-label Prediction Models—0
Advances of Deep Learning in Protein Science: A Comprehensive Survey—0
An application of topological graph clustering to protein function prediction—0
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All datasetsCASPSimSeqPaenSeqUniProtSeq

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GAL 120BROUGE-L0.25—Unverified
2GAL 30BROUGE-L0.14—Unverified
3GAL 6.7BROUGE-L0.11—Unverified
4GAL 1.3BROUGE-L0.07—Unverified
5GAL 125MROUGE-L0.06—Unverified
#ModelMetricClaimedVerifiedStatus
1GAL 120BROUGE-L0.27—Unverified
2GAL 30BROUGE-L0.2—Unverified
3GAL 6.7BROUGE-L0.14—Unverified
4GAL 1.3BROUGE-L0.08—Unverified
5GAL 125MROUGE-L0.07—Unverified
#ModelMetricClaimedVerifiedStatus
1GAL 120BROUGE-L0.25—Unverified
2GAL 30BROUGE-L0.19—Unverified
3GAL 6.7BROUGE-L0.11—Unverified
4GAL 1.3BROUGE-L0.08—Unverified
5GAL 125MROUGE-L0.06—Unverified