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 51–79 of 79 papers

TitleStatusHype
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
Multi-task Deep Neural Networks in Automated Protein Function Prediction—0
Multitask Protein Function Prediction Through Task Dissimilarity—0
PersGNN: Applying Topological Data Analysis and Geometric Deep Learning to Structure-Based Protein Function Prediction—0
Positive and Unlabeled Learning through Negative Selection and Imbalance-aware Classification—0
ProLanGO: Protein Function Prediction Using Neural~Machine Translation Based on a Recurrent Neural Network—0
ProtCLIP: Function-Informed Protein Multi-Modal Learning—0
Protein 3D Graph Structure Learning for Robust Structure-based Protein Property Prediction—0
MSNGO: multi-species protein function annotation based on 3D protein structure and network propagationCode0
Multi-modal Representation Learning Enables Accurate Protein Function Prediction in Low-Data SettingCode0
Graph Embedding on Biomedical Networks: Methods, Applications, and EvaluationsCode0
Ankh: Optimized Protein Language Model Unlocks General-Purpose ModellingCode0
Linear-scaling kernels for protein sequences and small molecules outperform deep learning while providing uncertainty quantitation and improved interpretabilityCode0
evoBPE: Evolutionary Protein Sequence TokenizationCode0
EurNet: Efficient Multi-Range Relational Modeling of Spatial Multi-Relational DataCode0
SCOP: A Sequence-Structure Contrast-Aware Framework for Protein Function PredictionCode0
AFDP: An Automated Function Description Prediction Approach to Improve Accuracy of Protein Function PredictionsCode0
Encoding protein dynamic information in graph representation for functional residue identificationCode0
ProtFAD: Introducing function-aware domains as implicit modality towards protein function predictionCode0
Biomedical Knowledge Graph Embeddings with Negative StatementsCode0
AnnoDPO: Protein Functional Annotation Learning with Direct Preference OptimizationCode0
Structure-Enhanced Meta-Learning For Few-Shot Graph ClassificationCode0
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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