| In Silico Approach To Identify Potential Thyroid Hormone Disruptors among Currently Known Dust Contaminants and Their Metabolites J Zhang, JH Kamstra, M Ghorbanzadeh, JM Weiss, T Hamers, ... Environmental science & technology 49 (16), 10099-10107, 2015 | 59 | 2015 |
| Modeling the cellular uptake of magnetofluorescent nanoparticles in pancreatic cancer cells: a quantitative structure activity relationship study M Ghorbanzadeh, MH Fatemi, M Karimpour Industrial & Engineering Chemistry Research 51 (32), 10712-10718, 2012 | 50 | 2012 |
| Binary classification model to predict developmental toxicity of industrial chemicals in zebrafish M Ghorbanzadeh, J Zhang, PL Andersson Journal of Chemometrics 30 (6), 298-307, 2016 | 23 | 2016 |
| Predictions of chromatographic retention indices of alkylphenols with support vector machines and multiple linear regression MH Fatemi, E Baher, M Ghorbanzade'h Journal of separation science 32 (23‐24), 4133-4142, 2009 | 22 | 2009 |
| Quantitative and qualitative prediction of corneal permeability for drug-like compounds M Ghorbanzad‘e, MH Fatemi, M Karimpour, PL Andersson Talanta 85 (5), 2686-2694, 2011 | 20 | 2011 |
| A QSRR study of liquid chromatography retention time of pesticides using linear and nonlinear chemometric models S Khodadoust, N Armand, S Masoudi, M Ghorbanzadeh J. Chromatogr. Sep. Tech 3 (07), 2012 | 17 | 2012 |
| Prediction of aqueous solubility of drug-like compounds by using an artificial neural network and least-squares support vector machine MH Fatemi, A Heidari, M Ghorbanzade Bulletin of the Chemical Society of Japan 83 (11), 1338-1345, 2010 | 16 | 2010 |
| Classification of drugs according to their milk/plasma concentration ratio MH Fatemi, M Ghorbanzad’e European journal of medicinal chemistry 45 (11), 5051-5055, 2010 | 16 | 2010 |
| In Vitro and in Silico Derived Relative Effect Potencies of Ah-Receptor-Mediated Effects by PCDD/Fs and PCBs in Rat, Mouse, and Guinea Pig CALUX Cell Lines M Ghorbanzadeh, KI Van Ede, M Larsson, MBM Van Duursen, ... Chemical Research in Toxicology 27 (7), 1120-1132, 2014 | 14 | 2014 |
| Classification of central nervous system agents by least squares support vector machine based on their structural descriptors: A comparative study M Ghorbanzad'e, MH Fatemi Chemometrics and Intelligent Laboratory Systems 110 (1), 102-107, 2012 | 14 | 2012 |
| In silico prediction of nematic transition temperature for liquid crystals using quantitative structure–property relationship approaches MH Fatemi, M Ghorbanzad’e Molecular diversity 13, 483-491, 2009 | 11 | 2009 |
| Quantitative structure retention relationship modeling of retention time for some organic pollutants MH Fatemi, M Ghorbanzad'e, E Baher Analytical letters 43 (5), 823-835, 2010 | 8 | 2010 |
Mohammad Hossien FatemiProfessor of chemistry, University of MazandaranBestätigte E-Mail-Adresse bei umz.ac.ir
