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    Integration of bioinformatics and cheminformatics for the analysis and classification of bioactive compounds used in cardiovascular diseases [Articol]
    (Editura USM, 2025) Aslanov, Rufat
    This paper presents a literature-based analysis on the integration of bioinformatics and chemoinformatics methods for identifying, classifying, and evaluating bioactive compounds with therapeutic potential in cardiovascular diseases. A detailed review of computational tools and molecular databases was conducted, emphasizing methods like QSAR modeling, virtual screening, and multi-omics integration. The research outlines a conceptual framework combining cheminformatics, bioinformatics, and machine learning techniques to enable efficient drug candidate classification and predictive modeling. The study concludes with directions for future research, particularly in enhancing data harmonization and model generalizability.