Search Results - Algamal, Z.Y.

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  1. 1
    Quantitative structure-activity relationship model for classifying the diverse series of antifungal agents using ratio weighted penalized logistic regression

    Quantitative structure-activity relationship model for classifying the diverse series of antifungal agents using ratio weighted penalized logistic regression by Alharthi, A.M., Lee, M.H., Algamal, Z.Y., Al-Fakih, A.M.

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  2. 2
    An improved opposition-based crow search algorithm for biodegradable material classification

    An improved opposition-based crow search algorithm for biodegradable material classification by Al-Fakih, A.M., Algamal, Z.Y., Qasim, M.K.

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  3. 3
    QSAR model for predicting neuraminidase inhibitors of influenza A viruses (H1N1) based on adaptive grasshopper optimization algorithm

    QSAR model for predicting neuraminidase inhibitors of influenza A viruses (H1N1) based on adaptive grasshopper optimization algorithm by Algamal, Z.Y., Qasim, M.K., Lee, M.H., Ali, H.T.M.

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  4. 4
    QSAR modelling of enzyme inhibition toxicity of ionic liquid based on chaotic spotted hyena optimization algorithm

    QSAR modelling of enzyme inhibition toxicity of ionic liquid based on chaotic spotted hyena optimization algorithm by Alharthi, A.M., Al-Thanoon, N.A., Al-Fakih, A.M., Algamal, Z.Y.

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  5. 5
    A robust quantitative structure-activity relationship modelling of influenza neuraminidase a/PR/8/34 (H1N1) inhibitors based on the rank-bridge estimator

    A robust quantitative structure-activity relationship modelling of influenza neuraminidase a/PR/8/34 (H1N1) inhibitors based on the rank-bridge estimator by Al-Dabbagh, Z.T., Algamal, Z.Y.

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  6. 6
    A binary QSAR model for classifying neuraminidase inhibitors of influenza A viruses (H1N1) using the combined minimum redundancy maximum relevancy criterion with the sparse support vector machine

    A binary QSAR model for classifying neuraminidase inhibitors of influenza A viruses (H1N1) using the combined minimum redundancy maximum relevancy criterion with the sparse support... by Qasim, M.K., Algamal, Z.Y., Ali, H.T. Mohammad

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  7. 7
    Quantitative structure-property relationship modelling for predicting retention indices of essential oils based on an improved horse herd optimization algorithm

    Quantitative structure-property relationship modelling for predicting retention indices of essential oils based on an improved horse herd optimization algorithm by Alharthi, A.M., Kadir, D.H., Al-Fakih, A.M., Algamal, Z.Y., Al-Thanoon, N.A., Qasim, M.K.

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  8. 8
    QSAR classification model for diverse series of antifungal agents based on binary coyote optimization algorithm

    QSAR classification model for diverse series of antifungal agents based on binary coyote optimization algorithm by Al-Fakih, A.M., Qasim, M.K., Algamal, Z.Y., Alharthi, A.M., Zainal-Abidin, M.H.

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  9. 9
    QSAR classification model for diverse series of antifungal agents based on improved binary differential search algorithm

    QSAR classification model for diverse series of antifungal agents based on improved binary differential search algorithm by Al-Fakih, A.M., Algamal, Z.Y., Lee, M.H., Aziz, M., Ali, H.T.M.

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  10. 10
    A QSAR model for predicting antidiabetic activity of dipeptidyl peptidase-IV inhibitors by enhanced binary gravitational search algorithm

    A QSAR model for predicting antidiabetic activity of dipeptidyl peptidase-IV inhibitors by enhanced binary gravitational search algorithm by Al-Fakih, A.M., Algamal, Z.Y., Lee, M.H., Aziz, M., Ali, H.T.M.

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