Z. Garkani-Nejad

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Application of multivariate image analysis in QSPR study of 13C chemical shifts of naphthalene derivatives: a comparative study.

Z. Garkani-Nejad, M. Poshteh-Shirani, 2010, Talanta.

Prediction of the anti-cancer activity of spiro derivatives of parthenin based on molecular modeling methods and docking

Zahra Garkani-Nejad, Z. Garkani-Nejad, M. Shahhoseini, 2014, Medicinal Chemistry Research.

Prediction of antihypertensive activity of pyridazinone derivatives through multivariate image analysis applied to QSAR

Z. Garkani-Nejad, M. Poshteh-Shirani, 2013, Medicinal Chemistry Research.

Erratum to: Comparative QSRR Modeling of Nitrobenzene Derivatives Based on Original Molecular Descriptors and Multivariate Image Analysis Descriptors

M. Ahmadvand, Z. Garkani-Nejad, 2011 .

A Comparative QSRR Study on Enantioseparation of Ethanol Ester Enantiomers in HPLC Using Multivariate Image Analysis, Quantum Mechanical and Structural Descriptors

Z. Garkani-Nejad, Hamideh Barfeii, 2017 .

Simultaneous estimation of stability constants of Mg, Ba, Ca, and Sr complexes using a small subset of molecular descriptors

M. Ahmadvand, Z. Garkani-Nejad, 2011 .

Investigation of the mechanism of enantioseparation of some drug compounds by considering the mobile phase in HPLC by molecular dynamics simulation

Z. Garkani-Nejad, V. Saheb, Hamideh Barfeii, 2019, Journal of Molecular Modeling.

Investigation of Linear and Nonlinear Chemometrics Methods in Modeling of Retention Time of Phenol Derivatives Based on Molecular Descriptors

M. Ahmadvand, Z. Garkani-Nejad, 2011 .

Prediction of Electrophoretic Mobilities of Organic Acids Using Artificial Neural Networks with Three Different Training Functions

Z. Garkani-Nejad, Seyedali Seyedbagheri, 2010 .

Research and study of 2-((4,6 dimethyl pyrimidine-2-yle) thio)-N-phenyl acetamide derivatives as inhibitors of sirtuin 2 protein for the treatment of cancer using QSAR, molecular docking and molecular dynamic simulation

Z. Garkani-Nejad, Sahar Ilaghi-Hoseini, 2022, Journal of Molecular Modeling.

Fabrication of platinum-doped NiCo2O4 nanograss modified electrode for determination of carbendazim.

Z. Garkani-Nejad, H. Akbari Javar, Hadi Mahmoudi-Moghaddam, 2022, Food chemistry.

Prediction of the anti-cancer activity of spiro derivatives of parthenin based on molecular modeling methods and docking

Z. Garkani-Nejad, Mehri Shahhoseini, 2014, Medicinal Chemistry Research.

A new electrochemical DNA biosensor for determination of anti-cancer drug chlorambucil based on a polypyrrole/flower-like platinum/NiCo2O4/pencil graphite electrode

Z. Garkani-Nejad, Hadi Mahmoudi-Moghaddam, 2022, RSC Advances.

Development of electrochemical biosensor for determination of antibiotic drug Isoniazid using ds-DNA/ Carbon/La3+/CuO/CPE

Z. Garkani-Nejad, Hadi Mahmoudi-Moghaddam, 2021, Measurement.

Z. Garkani-Nejad, Sahar Ilaghi-Hoseini, 2022, Journal of Molecular Modeling.

In silico study combining QSAR, docking and molecular dynamics simulation on 2,4-disubstituted pyridopyrimidine derivatives

Z. Garkani-Nejad, Maryam Tadayon, 2019, Journal of receptor and signal transduction research.

Development of a new electrochemical DNA biosensor based on Eu3+-doped NiO for determination of amsacrine as an anti-cancer drug: Electrochemical, spectroscopic and docking studies.

Z. Garkani-Nejad, H. Akbari Javar, Gholamreza Dehghannoudeh, 2020, Analytica chimica acta.

Grass-like Pt-doped NiCo2O4 modified electrode for electrochemical detection of amlodipine

Z. Garkani-Nejad, H. Akbari Javar, Hadi Mahmoudi-Moghaddam, 2022, Measurement.

An efficient sensor for simultaneous determination of Hg (II) and As (III) using a carbon paste electrode modified with needle-shaped Pt-doped NiCo2O4 nanograss

Z. Garkani-Nejad, H. A. Javar, Hadi Mahmoudi-Moghaddam, 2022, Sensors and Actuators B: Chemical.

Computational modeling and study of the anti-cancer activity of novel NSAID 1-acyl-4-cycloalkyl/arylsemicarbazide and 1-acyl-5-benzyloxy/hydroxy carbamoylcarbazide derivatives using molecular docking and molecular dynamics simulations

Z. Garkani-Nejad, Maryam Tadayon, 2018, Structural Chemistry.

A sensitive DNA biosensor for determination of mesalazine using PPy/Sponge-like Carbon/La3+-doped CuO nanocomposite

Z. Garkani-Nejad, Hadi Mahmoudi-Moghaddam, 2022, Journal of Materials Science: Materials in Electronics.

Investigation of MI-2 analogues as MALT1 inhibitors to treat of diffuse large B-Cell lymphoma through combined molecular dynamics simulation, molecular docking and QSAR techniques and design of new inhibitors

Z. Garkani-Nejad, Hossein Safarizadeh, 2019, Journal of Molecular Structure.

Application of multivariate image analysis in modeling 13C‐NMR chemical shifts of mono substituted pyridines

M. Ahmadvand, Z. Garkani-Nejad, 2012, Magnetic resonance in chemistry : MRC.

Use of Self-Training Artificial Neural Networks in a QSRR Study of a Diverse Set of Organic Compounds

Zahra Garkani-Nejad, Z. Garkani-Nejad, 2009 .

Molecular docking, molecular dynamics simulations and QSAR studies on some of 2-arylethenylquinoline derivatives for inhibition of Alzheimer's amyloid-beta aggregation: Insight into mechanism of interactions and parameters for design of new inhibitors.

Z. Garkani-Nejad, Hossein Safarizadeh, 2019, Journal of molecular graphics & modelling.

Prediction of electrophoretic mobilities of sulfonamides in capillary zone electrophoresis using artificial neural networks.

M. Jalali-Heravi, M Jalali-Heravi, Z Garkani-Nejad, 2001, Journal of chromatography. A.

Quantitative structure-activity relationship study using genetic algorithm-enhanced replacement method combined with molecular docking studies of isatin derivatives as inhibitors of human transglutaminase 2

Z. Garkani-Nejad, Maryam Tadayon, 2018, Journal of the Chinese Chemical Society.

Modeling the activity of 2-phenylnaphthalene inhibitors using self-training artificial neural networks

Z. Garkani-Nejad, Naser Jalili-Jahani, 2010 .

Prediction of gas chromatographic retention indices of a diverse set of toxicologically relevant compounds.

W Vycudilik, K Varmuza, T Stimpfl, 2004, Journal of chromatography. A.

Modeling the antileishmanial activity screening of 5-nitro-2-heterocyclic benzylidene hydrazides using different chemometrics methods.

Zahra Garkani-Nejad, Behzad Ahmadi-Roudi, Z. Garkani-Nejad, 2010, European journal of medicinal chemistry.

Electrochemical Determination of Levodopa and Cabergoline by a Magnetic Core-Shell Iron (II,III) Oxide@Silica/Multiwalled Carbon Nanotube/Ionic Liquid/2-(4-Oxo-3-Phenyl-3,4-Dihydroquinazolinyl)- N′-Phenyl-Hydrazine Carbothioamide (FSCNT/IL/2PHC) Modified Carbon Paste Electrode

H. Beitollahi, S. Tajik, Z. Garkani-Nejad, 2021 .

Comparison of conventional artificial neural network and wavelet neural network in modeling the half-wave potential of aldehydes and ketones

Zahra Garkani-Nejad, Z. Garkani-Nejad, Hamid Rashidi-Nodeh, 2010 .

Quantitative structure-retention relationship study of some phenol derivatives in gas chromatography.

Z. Garkani-Nejad, 2010, Journal of chromatographic science.

Prediction of electrophoretic mobilities of alkyl- and alkenylpyridines in capillary electrophoresis using artificial neural networks.

M. Jalali-Heravi, Z. Garkani-Nejad, 2002, Journal of chromatography. A.

Prediction of relative response factors for flame ionization and photoionization detection using self-training artificial neural networks.

M. Jalali-Heravi, M Jalali-Heravi, Z Garkani-Nejad, 2002, Journal of chromatography. A.

Prediction of antihypertensive activity of pyridazinone derivatives through multivariate image analysis applied to QSAR

Z. Garkani-Nejad, M. Poshteh-Shirani, 2013, Medicinal Chemistry Research.

Comparative QSRR Modeling of Nitrobenzene Derivatives Based on Original Molecular Descriptors and Multivariate Image Analysis Descriptors

M. Ahmadvand, Z. Garkani-Nejad, 2011 .

3D protein structure prediction using Imperialist Competitive algorithm and half sphere exposure prediction.

Erfan Khaji, Masoumeh Karami, Zahra Garkani-Nejad, 2016, Journal of theoretical biology.

Use of self-training artificial neural networks in modeling of gas chromatographic relative retention times of a variety of organic compounds.

M. Jalali-Heravi, M Jalali-Heravi, Z Garkani-Nejad, 2002, Journal of chromatography. A.