Схожі ресурси

• In Silico Functional Profiling of Engineered Small Molecules: A Machine Learning Approach Leveraging PubChem Identifiers (CID_SID ML model)
  за авторством: Ivanova, Mariya L., та інші
  Опубліковано: (2025)
• IUPAC-Induced Computational Approaches for Identifying Boosters of Small Biomolecule Functionality: A Case Study of Human Tyrosyl-DNA Phosphodiesterase 1 (TDP1) Inhibitors
  за авторством: Ivanova, Mariya L., та інші
  Опубліковано: (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
  за авторством: Ivanova, Mariya L., та інші
  Опубліковано: (2025)
• Comparative analysis of computational approaches for predicting Transthyretin (TTR) transcription activators and human dopamine D1 receptor antagonists
  за авторством: Ivanova, Mariya L., та інші
  Опубліковано: (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
  за авторством: Ivanova, Mariya L, та інші
  Опубліковано: (2025)