Halima Bazoui

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QSARs were derived for 103 analogues of 1-[(2-hydroxyethoxy)methyl]-6-(phenylthio)thymine (HEPT), a potent inhibitor of the HIV-1 reverse transcriptase (RT). The activity of these compounds was investigated by means of multiple linear regression (MLR) and artificial neural network (ANN) techniques. Considering the relevant descriptors obtained from the MLR,(More)
Structure-toxicity relationships were studied for a set of 47 insecticides by means of multiple linear regression (MLR) and artificial neural network (ANN). A model with three descriptors, including shape surface [S(R2)], hydrogen-bonding acceptors [HBA(R2)] and molar refraction [MR(R1)], showed good statistics both in the regression (r = 0.875, s = 0.417(More)
INTRODUCTION Tuberculosis is a major public health threat, annually affecting new individuals worldwide, especially those in developing countries. Rapid detection of the agent and effective treatment are two important factors in controlling this disease. METHODOLOGY The present study aimed to evaluate polymerase chain reaction (PCR) as a rapid and direct(More)
Structure-cytotoxicity relationships were studied for a series of 90 HEPT derivatives by means of multiple linear regression (MLR) and artificial neural network (ANN) techniques. The values of log(1/CC50) (CC50=cytotoxic dose of compound required to reduce the proliferation of normal uninfected MT-4 cells by 50%) of the studied compounds were correlated(More)
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