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11 ta ish

Ish: Beware of q2!

  1. New tyrosinase inhibitors selected by atomic linear indices-based classification models

    Gerardo M. Casañola‐Martín, Mahmud Tareq Hassan Khan, Yovani Marrero‐Ponce +3

    MaqolaComputational Drug Discovery MethodsBioorganic & Medicinal Chemistry Letters20051 iqtibos
    ABI

  2. SMILES‐based optimal descriptors: QSAR analysis of fullerene‐based HIV‐1 PR inhibitors by means of balance of correlations

    Andrey A. Toropov, Alla P. Toropova, Emilio Benfenati +2

    MaqolaComputational Drug Discovery MethodsJournal of Computational Chemistry20091 iqtibos
    ABI

  3. QSAR modelling of carcinogenicity by balance of correlations

    Andrey A. Toropov, Alla P. Toropova, Emilio Benfenati +1

    MaqolaAdvanced Chemical Sensor TechnologiesMolecular Diversity20091 iqtibos
    ABI

  4. Atom‐Based 2D Quadratic Indices in Drug Discovery of Novel Tyrosinase Inhibitors: Results of <i>In Silico</i> Studies Supported by Experimental Results

    Yovani Marrero Ponce, Mahmud Tareq Hassan Khan, Gerardo M. Casañola‐Martín +5

    MaqolaComputational Drug Discovery MethodsQSAR & Combinatorial Science20061 iqtibos
    ABI

  5. Bond-based 2D TOMOCOMD-CARDD approach for drug discovery: aiding decision-making in ‘in silico’ selection of new lead tyrosinase inhibitors

    Yovani Marrero‐Ponce, Mahmud Tareq Hassan Khan, Gerardo M. Casañola‐Martín +5

    MaqolaComputational Drug Discovery MethodsJournal of Computer-Aided Molecular Design20070 iqtibos
    ABI

  6. QSPR modeling of enthalpies of formation for organometallic compounds by SMART‐based optimal descriptors

    Andrey A. Toropov, Alla P. Toropova, Emilio Benfenati +1

    MaqolaComputational Drug Discovery MethodsJournal of Computational Chemistry20090 iqtibos
    ABI

  7. InChI-based optimal descriptors: QSAR analysis of fullerene[C60]-based HIV-1 PR inhibitors by correlation balance

    Andrey A. Toropov, Alla P. Toropova, Emilio Benfenati +2

    MaqolaComputational Drug Discovery MethodsEuropean Journal of Medicinal Chemistry20100 iqtibos
    ABI

  8. The Monte Carlo Method Based on Eclectic Data as an Efficient Tool for Predictions of Endpoints for Nanomaterials - Two Examples of Application

    Andrey A. Toropov, Alla P. Toropova, Aleksandar M. Veselinović +8

    MaqolaComputational Drug Discovery MethodsCombinatorial Chemistry & High Throughput Screening20150 iqtibos
    ABI

  9. Mathematical modeling of refractive index based on machine learning (kNN-QSPR) method

    Rifkat Davronov, Bakhtiyor Rasulev, Fatima Аdilova

    MaqolaComputational Drug Discovery Methods20200 iqtibos
    ABI

  10. Quantitative Structure─Permittivity Relationship Study of a Series of Polymers

    Yevhenii Zhuravskyi, Kweeni Iduoku, Meade Erickson +8

    MaqolaDielectric materials and actuatorsACS Materials Au20240 iqtibos
    ABI

  11. Predictive modeling for compressive strength of blended cement concrete using hybrid machine learning models

    Asad Ullah Khan, Raheel Asghar, Najmul Hassan +4

    MaqolaInnovative concrete reinforcement materialsMultiscale and Multidisciplinary Modeling Experiments and Design20240 iqtibos
    ABI