articleBioData MiningFeb 3, 2025GOLD OA

XGBoost-enhanced ensemble model using discriminative hybrid features for the prediction of sumoylation sites

King Saud University · Purdue University West Lafayette · +4 more institutions

PubMed
Indexed incrossrefdoajpubmed

Abstract

Posttranslational modifications (PTMs) are essential for regulating protein localization and stability, significantly affecting gene expression, biological functions, and genome replication. Among these, sumoylation a PTM that attaches a chemical group to protein sequences-plays a critical role in protein function. Identifying sumoylation sites is particularly important due to their links to Parkinson's and Alzheimer's. This study introduces XGBoost-Sumo, a robust model to predict sumoylation sites by integrating protein structure and sequence data. The model utilizes a transformer-based attention mechanism to encode peptides and extract evolutionary features through the PsePSSM-DWT approach. By fusing word…

Citation impact

49
total citations
FWCI
31.43
Percentile
100%
References
60
Citations per year

Authors

7

Topics & keywords

Keywords
  • Discriminative model
  • SUMO protein
  • Computer science
  • Ensemble forecasting
  • Artificial intelligence
  • Machine learning
  • Chemistry
UN Sustainable Development Goals
  • Reduced inequalities
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