Advancements in QSAR modelling: Decision trees and rotation forest for prediction of Aspergillus anti-inflammatory metabolites

Vol 9, 2023 - 167363
Poster
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Abstract

The study showcased advancements in Quantitative Structure Activity Relationship (QSAR) modelling, employing decision trees and rotation forest to accurately predict nitric oxide (NO) inhibitors and anti-inflammatory metabolites from Aspergillus fungi species. Leveraging an ensemble approach, the research offers strategies for enhanced machine learning NO anti-inflammatory models for drug discovery.

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Institutions
  • 1 Universidade Federal de Alfenas
  • 2 Universidade Federal de Sergipe
  • 3 Federal University of Sergipe
Track
  • 5. Recent Advances in the Isolation and Structure Elucidation of Secondary Metabolites
Keywords
J48 Algorithm; Ensemble Methods; Machine Learning