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Table 4 Fivefold cross validation results (mean ± one standard deviation) of different models based on ProtT5 features

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

Architecture

ACC

SN

SP

MCC

ANN

0.710 ± 0.015

0.745 ± 0.028

0.674 ± 0.015

0.421 ± 0.030

SVM

0.700 ± 0.012

0.702 ± 0.016

0.699 ± 0.020

0.401 ± 0.024

RF

0.682 ± 0.010

0.815 ± 0.815

0.549 ± 0.815

0.379 ± 0.378

XGBoost

0.699 ± 0.008

0.752 ± 0.019

0.645 ± 0.007

0.400 ± 0.016

AdaBoost

0.672 ± 0143

0.695 ± 0.024

0.650 ± 0.022

0.345 ± 0.029

  1. Highest values in each column are highlighted in bold
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BMC Bioinformatics

ISSN: 1471-2105

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