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Protein Secondary Structure Prediction On 1

評価指標

Q3
Q8

評価結果

このベンチマークにおける各モデルのパフォーマンス結果

モデル名
Q3
Q8
Paper TitleRepository
ProtT5-XL-UniRef500.860.74ProtTrans: Towards Cracking the Language of Life's Code Through Self-Supervised Deep Learning and High Performance Computing-
ProtT5-XL-BFD0.840.71ProtTrans: Towards Cracking the Language of Life's Code Through Self-Supervised Deep Learning and High Performance Computing-
Porter5-0.74Deeper Profiles and Cascaded Recurrent and Convolutional Neural Networks for state-of-the-art Protein Secondary Structure Prediction
LucaAngioloni-WindowCNN-0.684Protein secondary structure prediction using deep convolutional neural fields-
Advanced ACNN-0.733--
ACNN-0.697Protein secondary structure prediction using deep convolutional neural fields-
PS4-Mega0.8680.763PS4: a Next-Generation Dataset for Protein Single Sequence Secondary Structure Prediction
PS4-Conv0.8630.756PS4: a Next-Generation Dataset for Protein Single Sequence Secondary Structure Prediction
ProtBert-BFD0.830.7ProtTrans: Towards Cracking the Language of Life's Code Through Self-Supervised Deep Learning and High Performance Computing-
DistilProtBert0.79-DistilProtBert: A distilled protein language model used to distinguish between real proteins and their randomly shuffled counterparts
0 of 10 row(s) selected.