The QSAR analysis of acute intravenous toxicity for mice of 68 monofunctional chemical compounds is presented. These compounds are referred to seven chemical classes: hydrocarbons (6 chemicals), alcohols (13), amides (22), amines (12), ethers (5), ketones (7), and nitriles (3). Preliminary consideration of data for these chemical compounds showed the necessity of consideration of nonlinear toxicity – descriptor relationships in addition to linear toxicity – descriptor relationships. The linear and nonlinear QSAR models were considered for each indicated class of organic chemical compounds. Analogical models were constructed for the whole set of the monofunctional chemical compounds. The statistical parameters and robustness of nonlinear mod...
Quantitative structure-activity relationship (QSAR) models are widely used for in silico prediction ...
A simple approach is introduced to assess the toxicity of nitroaromatic compounds in terms of an ora...
Few Quantitative Structure-Activity Relationship (QSAR) studies have successfully modeled large, div...
Modeling of quantitative structure — activity relationships (QSAR) between physicochemical descripto...
This paper reviews Quantitative Structure-Activity Relationship (QSAR) models for acute mammalian to...
1 Abstract The goal of the thesis is to determine acute toxicity indices of seven alcohols (2-ethoxy...
The information of the acute oral toxicity for most polycyclic aromatic hydrocarbons (PAHs) in mamma...
Future EU legislations enforce a fast hazard and risk assessment of thousands of existing chemicals....
Predicting toxicity quantitatively, using Quantitative Structure Activity Relationships (QSAR), has ...
This paper reviews Quantitative Structure-Activity Relationship (QSAR) models for acute mammalian to...
A novel modelling approach based on the structural and physicochemical similarity of chemicals to th...
To better understand the mechanism of in vivo toxicity of N-nitroso compounds (NNCs), the toxicity d...
In this project quantitative structure-activity relationships (QSARs) were developed for several tox...
Over the past decades the description of quantitative structure–activity relationships (QSARs) has b...
LD50 tests on rat and mouse are commonly used to express the relative hazard associated with the acu...
Quantitative structure-activity relationship (QSAR) models are widely used for in silico prediction ...
A simple approach is introduced to assess the toxicity of nitroaromatic compounds in terms of an ora...
Few Quantitative Structure-Activity Relationship (QSAR) studies have successfully modeled large, div...
Modeling of quantitative structure — activity relationships (QSAR) between physicochemical descripto...
This paper reviews Quantitative Structure-Activity Relationship (QSAR) models for acute mammalian to...
1 Abstract The goal of the thesis is to determine acute toxicity indices of seven alcohols (2-ethoxy...
The information of the acute oral toxicity for most polycyclic aromatic hydrocarbons (PAHs) in mamma...
Future EU legislations enforce a fast hazard and risk assessment of thousands of existing chemicals....
Predicting toxicity quantitatively, using Quantitative Structure Activity Relationships (QSAR), has ...
This paper reviews Quantitative Structure-Activity Relationship (QSAR) models for acute mammalian to...
A novel modelling approach based on the structural and physicochemical similarity of chemicals to th...
To better understand the mechanism of in vivo toxicity of N-nitroso compounds (NNCs), the toxicity d...
In this project quantitative structure-activity relationships (QSARs) were developed for several tox...
Over the past decades the description of quantitative structure–activity relationships (QSARs) has b...
LD50 tests on rat and mouse are commonly used to express the relative hazard associated with the acu...
Quantitative structure-activity relationship (QSAR) models are widely used for in silico prediction ...
A simple approach is introduced to assess the toxicity of nitroaromatic compounds in terms of an ora...
Few Quantitative Structure-Activity Relationship (QSAR) studies have successfully modeled large, div...