Showing 1 - 20 results of 227 for search '"cheminformatics"', query time: 0.08s Refine Results
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    Milestones in cheminformatics by Karina Martinez-Mayorga, José L. Medina-Franco

    Published 2025-07-01
    “…Journal of Cheminformatics…”
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    Cheminformatics Models for Inhibitors of Schistosoma mansoni Thioredoxin Glutathione Reductase by Sonam Gaba, Salma Jamal, Open Source Drug Discovery Consortium, Vinod Scaria

    Published 2014-01-01
    “…We show that a combined approach of machine learning and other cheminformatics approaches such as substructure comparison and molecular docking is efficient to prioritise molecules from large molecular datasets.…”
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    Regional Explanations and Diverse Molecular Representations in Cheminformatics: A Comparative Study by Xin Wang, Amanda S. Barnard, Sichao Li

    Published 2025-01-01
    “…In cheminformatics, the explainability of machine learning models is important for interpreting complex chemical data, deriving new chemical insights, and building trust in predictive models. …”
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    Inverse link prediction with graph convolutional networks for knowledge-preserving sparsification in cheminformatics by Elnaz Bangian Tabrizi, Mehrdad Jalali, Mahboobeh Houshmand

    Published 2025-07-01
    “…Abstract Large-scale cheminformatics datasets, such as those used in drug discovery and materials science, are often represented as dense similarity graphs; however, their complexity hinders scalable analysis and interpretability. …”
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    Cheminformatics-aided discovery of potential allosteric site modulators of ubiquitin-specific protease 7 by Olayinka Abraham Ojedele, Haruna Isiyaku Umar, Soukayna baammi, Amira Metouekel, Atrsaw Asrat Mengistie, Yousef A. Bin Jardan, Gamal A. Shazly, Omoboyede Victor

    Published 2024-10-01
    “…In this study, molecular modeling techniques and cheminformatics approaches were employed to unravel the potential of eighty compounds to serve as its allosteric site modulators. …”
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    Molecular Recognition of SARS-CoV-2 Mpro Inhibitors: Insights from Cheminformatics and Quantum Chemistry by Adedapo Olosunde, Xiche Hu

    Published 2025-05-01
    “…Cheminformatics analysis revealed distinct physicochemical profiles for each inhibitor class: covalent inhibitors tend to exhibit higher hydrogen bonding capacity and sp<sup>3</sup> character, while non-covalent inhibitors are enriched in aromatic rings and exhibit greater aromaticity and lipophilicity. …”
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