Sani Uba
Ahmadu Bello University
[ 1 ] - A Novel QSAR Model for the Evaluation and Prediction of (E)-N’-Benzylideneisonicotinohydrazide Derivatives as the Potent Anti-mycobacterium Tuberculosis Antibodies Using Genetic Function Approach
Abstract A dataset of (E)-N’-benzylideneisonicotinohydrazide derivatives as a potent anti-mycobacterium tuberculosis has been investigated utilizing Quantitative Structure-Activity Relationship (QSAR) techniques. Genetic Function Algorithm (GFA) and Multiple Linear Regression Analysis (MLRA) were used to select the descriptors and to generate the correlation QSAR models that relate the Mi...
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