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 1–10 of 79 papers

TitleStatusHype
AnnoDPO: Protein Functional Annotation Learning with Direct Preference OptimizationCode0
Into the Unknown: From Structure to Disorder in Protein Function Prediction—0
STELLA: Towards Protein Function Prediction with Multimodal LLMs Integrating Sequence-Structure Representations—0
MSNGO: multi-species protein function annotation based on 3D protein structure and network propagationCode0
evoBPE: Evolutionary Protein Sequence TokenizationCode0
ProtTeX: Structure-In-Context Reasoning and Editing of Proteins with Large Language Models—0
Computational Protein Science in the Era of Large Language Models (LLMs)—0
GoBERT: Gene Ontology Graph Informed BERT for Universal Gene Function Prediction—0
ProtCLIP: Function-Informed Protein Multi-Modal Learning—0
ProtBoost: protein function prediction with Py-Boost and Graph Neural Networks -- CAFA5 top2 solutionCode1
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All datasetsCASPSimSeqPaenSeqUniProtSeq

Benchmark Results

#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