Lignende værker

• Targeting Neurodegeneration: Three Machine Learning Methods for G9a Inhibitors Discovery Using PubChem and Scikit-learn
  af: Ivanova, Mariya L., et al.
  Udgivet: (2025)
• IUPAC-Induced Computational Approaches for Identifying Boosters of Small Biomolecule Functionality: A Case Study of Human Tyrosyl-DNA Phosphodiesterase 1 (TDP1) Inhibitors
  af: Ivanova, Mariya L., et al.
  Udgivet: (2025)
• Machine Learning - driven insights for predicting the impact of nanoparticles on the functionality of biomolecules, Illustrated by the case of DNA Damage-Inducible Transcript 3 (CHOP) inhibitors
  af: Ivanova, Mariya L., et al.
  Udgivet: (2025)
• Comparative analysis of computational approaches for predicting Transthyretin (TTR) transcription activators and human dopamine D1 receptor antagonists
  af: Ivanova, Mariya L., et al.
  Udgivet: (2025)
• Machine learning model leveraging SMILES-derived NMR spectroscopy data to predict dopamine D1 receptor antagonists: a prospective framework for forecasting the impact of engineered nanoparticles on the functionalities of small biomolecules
  af: Ivanova, Mariya L, et al.
  Udgivet: (2025)