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Table 6 Performance comparison of base models (aka Embedding2DCNN and ProtT5ANN models) and ensemble model (pLMSNOSite)

From: pLMSNOSite: an ensemble-based approach for predicting protein S-nitrosylation sites by integrating supervised word embedding and embedding from pre-trained protein language model

Models

ACC

SN

SP

MCC

Embedding2DCNN

0.706

0.798

0.696

0.310

ProtT5ANN

0.791

0.598

0.812

0.293

pLMSNOSite

0.769

0.735

0.772

0.340

  1. The highest value in each column is highlighted in bold
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BMC Bioinformatics

ISSN: 1471-2105

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