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Predicting Toxicities of Diverse Chemical Pesticides in Multiple Avian Species Using Tree-Based QSAR Approaches for Regulatory Purposes

Journal of chemical information and modeling, 2015-07, Vol.55 (7), p.1337-1348

2015

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Predicting human intestinal absorption of diverse chemicals using ensemble learning based QSAR modeling approaches

Computational biology and chemistry, 2016-04, Vol.61, p.178-196

2016

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Multi-target QSPR modeling for simultaneous prediction of multiple gas-phase kinetic rate constants of diverse chemicals

Atmospheric environment (1994), 2018-03, Vol.177, p.166-174

2018

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Predictive modeling: Solubility of C 60 and C 70 fullerenes in diverse solvents

Chemosphere (Oxford), 2018-06, Vol.201, p.361

2018

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Modeling the aqueous phase reactivity of hydroxyl radical towards diverse organic micropollutants: An aid to water decontamination processes

Chemosphere (Oxford), 2017-10, Vol.185, p.1164-1172

2017

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Predictive modeling: Solubility of C60 and C70 fullerenes in diverse solvents

Chemosphere (Oxford), 2018-06, Vol.201, p.361-369

2018

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Multi-target QSTR modeling for simultaneous prediction of multiple toxicity endpoints of nano-metal oxides

Nanotoxicology, 2017-04, Vol.11 (3), p.339-350

2017

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Modeling the pH and temperature dependence of aqueousphase hydroxyl radical reaction rate constants of organic micropollutants using QSPR approach

Environmental science and pollution research international, 2017-11, Vol.24 (32), p.24936-24946

2017

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QSAR modeling for predicting mutagenic toxicity of diverse chemicals for regulatory purposes

Environmental science and pollution research international, 2017-06, Vol.24 (16), p.14430-14444

2017

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Modeling the reactivity of ozone and sulphate radicals towards organic chemicals in water using machine learning approaches

RSC advances, 2016-01, Vol.6 (110), p.108448-108457

2016

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Modeling uptake of nanoparticles in multiple human cells using structure-activity relationships and intercellular uptake correlations

Nanotoxicology, 2017-02, Vol.11 (1), p.20-30

2017

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Support vector machines in water quality management

Analytica chimica acta, 2011-10, Vol.703 (2), p.152-162

2011

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Discovery of a Novel HDAC2 Inhibitor by a Scaffold-Merging Hybrid Query

Combinatorial chemistry & high throughput screening, 2015-01, Vol.18 (7), p.693-700

2015

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Predicting aquatic toxicities of chemical pesticides in multiple test species using nonlinear QSTR modeling approaches

Chemosphere (Oxford), 2015-11, Vol.139, p.246-255

2015

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In silico prediction of cellular permeability of diverse chemicals using qualitative and quantitative SAR modeling approaches

Chemometrics and intelligent laboratory systems, 2015-01, Vol.140, p.61-72

2015

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Nickel and cadmium phytoextraction efficiencies of vetiver and lemongrass grown on Ni–Cd battery waste contaminated soil: A comparative study of linear and nonlinear models

Journal of environmental management, 2021-10, Vol.295, p.113144-113144, Article 113144

2021

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Predicting acetyl cholinesterase enzyme inhibition potential of ionic liquids using machine learning approaches: An aid to green chemicals designing

Journal of molecular liquids, 2015-09, Vol.209, p.404-412

2015

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Recovery of precious metals from e-wastes through conventional and phytoremediation treatment methods: a review and prediction

Journal of material cycles and waste management, 2023-09, Vol.25 (5), p.2726-2752

2023

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QSTR modeling for predicting aquatic toxicity of pharmacological active compounds in multiple test species for regulatory purpose

Chemosphere (Oxford), 2015-02, Vol.120, p.680-689

2015

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Linear and nonlinear modeling for simultaneous prediction of dissolved oxygen and biochemical oxygen demand of the surface water — A case study

Chemometrics and intelligent laboratory systems, 2010-12, Vol.104 (2), p.172-180

2010

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Three-Tier Strategy for Screening High-Energy Molecules Using Structure–Property Relationship Modeling Approaches

Industrial & engineering chemistry research, 2016-01, Vol.55 (3), p.820-831

2016

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Predicting the acute neurotoxicity of diverse organic solvents using probabilistic neural networks based QSTR modeling approaches

Neurotoxicology (Park Forest South), 2016-03, Vol.53, p.45-52

2016

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Reducing Arsenic Uptake in Cereal Crop Plants with Sugarcane Waste Application: A Comparative Study on the Effects on Physiology, Biochemistry, and Grain Nutrient Status

Journal of plant growth regulation, 2023-10, Vol.42 (10), p.6835-6852

2023

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QSTR Modeling for Qualitative and Quantitative Toxicity Predictions of Diverse Chemical Pesticides in Honey Bee for Regulatory Purposes

Chemical research in toxicology, 2014-09, Vol.27 (9), p.1504-1515

2014

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A three-tier QSAR modeling strategy for estimating eye irritation potential of diverse chemicals in rabbit for regulatory purposes

Regulatory toxicology and pharmacology, 2016-06, Vol.77, p.282-291

2016

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Predicting Toxicities of Diverse Chemical Pesticides in Multiple Avian Species Using Tree-Based QSAR Approaches for Regulatory Purposes

Predicting human intestinal absorption of diverse chemicals using ensemble learning based QSAR modeling approaches

Multi-target QSPR modeling for simultaneous prediction of multiple gas-phase kinetic rate constants of diverse chemicals

Predictive modeling: Solubility of C 60 and C 70 fullerenes in diverse solvents

Modeling the aqueous phase reactivity of hydroxyl radical towards diverse organic micropollutants: An aid to water decontamination processes

Predictive modeling: Solubility of C60 and C70 fullerenes in diverse solvents

Multi-target QSTR modeling for simultaneous prediction of multiple toxicity endpoints of nano-metal oxides

Modeling the pH and temperature dependence of aqueousphase hydroxyl radical reaction rate constants of organic micropollutants using QSPR approach

QSAR modeling for predicting mutagenic toxicity of diverse chemicals for regulatory purposes

Modeling the reactivity of ozone and sulphate radicals towards organic chemicals in water using machine learning approaches

Modeling uptake of nanoparticles in multiple human cells using structure-activity relationships and intercellular uptake correlations

Support vector machines in water quality management

Discovery of a Novel HDAC2 Inhibitor by a Scaffold-Merging Hybrid Query

Predicting aquatic toxicities of chemical pesticides in multiple test species using nonlinear QSTR modeling approaches

In silico prediction of cellular permeability of diverse chemicals using qualitative and quantitative SAR modeling approaches

Nickel and cadmium phytoextraction efficiencies of vetiver and lemongrass grown on Ni–Cd battery waste contaminated soil: A comparative study of linear and nonlinear models

Predicting acetyl cholinesterase enzyme inhibition potential of ionic liquids using machine learning approaches: An aid to green chemicals designing

Recovery of precious metals from e-wastes through conventional and phytoremediation treatment methods: a review and prediction

QSTR modeling for predicting aquatic toxicity of pharmacological active compounds in multiple test species for regulatory purpose

Linear and nonlinear modeling for simultaneous prediction of dissolved oxygen and biochemical oxygen demand of the surface water — A case study

Three-Tier Strategy for Screening High-Energy Molecules Using Structure–Property Relationship Modeling Approaches

Predicting the acute neurotoxicity of diverse organic solvents using probabilistic neural networks based QSTR modeling approaches

Reducing Arsenic Uptake in Cereal Crop Plants with Sugarcane Waste Application: A Comparative Study on the Effects on Physiology, Biochemistry, and Grain Nutrient Status

QSTR Modeling for Qualitative and Quantitative Toxicity Predictions of Diverse Chemical Pesticides in Honey Bee for Regulatory Purposes

A three-tier QSAR modeling strategy for estimating eye irritation potential of diverse chemicals in rabbit for regulatory purposes

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