Ivanova, Mariya and Nicholls, Michael (2025) Is it time to treat AI as a creature? AI&Society. (Submitted)
    Ivanova, Mariya, Russo, Nicola, Mihaylov, Gueorgui and Konstantin, Nikolic ORCID: https://orcid.org/0000-0002-6551-2977
  
(2025)
Comparative analysis of computational approaches for predicting human neuronal Transthyretin (TTR) transcription activators and human dopamine D1 receptor antagonists.
    Journal of Cellular Biochemistry.
    
     ISSN 0730-2312
  
   (Submitted)
    Ivanova, Mariya, Russo, Nicola, Mihaylov, Gueorgui and Konstantin, Nikolic ORCID: https://orcid.org/0000-0002-6551-2977
  
(2025)
Comparative analysis of computational approaches for predicting human neuronal Transthyretin (TTR) transcription activators and human dopamine D1 receptor antagonists.
    Journal of Cellular Biochemistry.
    
     ISSN 0730-2312
  
   (Submitted)
    Ivanova, Mariya, Russo, Nicola, Mihaylov, Gueorgui and Konstantin, Nikolic ORCID: https://orcid.org/0000-0002-6551-2977
  
(2025)
Leveraging Machine Learning and IUPAC names to identify TDP1 inhibitors.
    Computational and Structural Biotechnology.
    
    
  
   (Submitted)
    Ivanova, Mariya, Russo, Nicola, Mihaylov, Gueorgui and Konstantin, Nikolic ORCID: https://orcid.org/0000-0002-6551-2977
  
(2025)
Leveraging Machine Learning and IUPAC names to identify TDP1 inhibitors.
    Computational and Structural Biotechnology.
    
    
  
   (Submitted)
    Ivanova, Mariya, Russo, Nicola, Mihaylov, Gueorgui and Konstantin, Nikolic ORCID: https://orcid.org/0000-0002-6551-2977
  
(2025)
Leveraging 13C NMR spectrum data derived from SMILES for machine learning-based prediction of a small biomolecule functionality: a case study on human Dopamine D1 receptor antagonists.
    Advance Intelligent Discovery.
    
    
  
   (Submitted)
    Ivanova, Mariya, Russo, Nicola, Mihaylov, Gueorgui and Konstantin, Nikolic ORCID: https://orcid.org/0000-0002-6551-2977
  
(2025)
Leveraging 13C NMR spectrum data derived from SMILES for machine learning-based prediction of a small biomolecule functionality: a case study on human Dopamine D1 receptor antagonists.
    Advance Intelligent Discovery.
    
    
  
   (Submitted)
    Ivanova, Mariya, Russo, Nicola, Mihaylov, Gueorgui and Konstantin, Nikolic ORCID: https://orcid.org/0000-0002-6551-2977
  
(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.
    IEEE Transactions on Pattern Analysis and Machine Intelligence.
    
     ISSN 0162-8828
  
   (Submitted)
    Ivanova, Mariya, Russo, Nicola, Mihaylov, Gueorgui and Konstantin, Nikolic ORCID: https://orcid.org/0000-0002-6551-2977
  
(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.
    IEEE Transactions on Pattern Analysis and Machine Intelligence.
    
     ISSN 0162-8828
  
   (Submitted)
    Ivanova, Mariya, Russo, Nicola and Nikolic, Konstantin ORCID: https://orcid.org/0000-0002-6551-2977
  
(2025)
Targeting neurodegeneration: three machine learning methods for G9a inhibitors discovery using PubChem and scikit-learn.
    Journal of Computer-Aided Molecular Design, 39 (1).
    
     ISSN 0920-654X
  
  
    Ivanova, Mariya, Russo, Nicola, Mihaylov, Gueorgui and Konstantin, Nikolic ORCID: https://orcid.org/0000-0002-6551-2977
  
(2025)
Predicting novel functional roles of designed small biomolecules: an ML Approach utilizing PubChem Compound and Substance Identifiers (CID-SID ML model).
    In Silico Pharmacology.
    
    
  
   (Submitted)