JRC QSAR Model Database models and data: Recent submissions

Showing items 21-28 of 28

Benigni, R.; Bossa, C.; Netzeva, T. I.; Rodomonte, A.; Tsakovska, I. Mechanistic QSAR of aromatic amines: New models for discriminating between homocyclic mutagens and nonmutagens, and validation of models for carcinogens. Environ. Mol. Mutagen. 2007, 48, 754–771.

Published: Alfonso T. Garcia-Sosa (2015-03-23)

Abstract: Because of its environmental and industrial importance, the aromatic amines are the single chemical class most studied for its ability to induce mutations and cancer. The large database of mutagenicity and carcinogenicity results has been studied with Quantitative Structure-Activity Relationship (QSAR) approaches by several authors, leading to models for the ...

HumanHealth Regression QMRF
Gramatica, P.; Giani, E.; Papa, E. Statistical external validation and consensus modeling: A QSPR case study for Koc prediction. J. Mol. Graph. Model. 2007, 25, 6, 755–766.

Published: Iiris Kahn (2015-01-27)

Abstract: The soil sorption partition coefficient (log Koc) of a heterogeneous set of 643 organic non-ionic compounds, with a range of more than 6 log units, is predicted by a statistically validated QSAR modeling approach. The applied multiple linear regression (ordinary least squares, OLS) is based on a variety of theoretical molecular descriptors selected by the ...

EnvironFate Regression QMRF
Enoch, S.J.; Cronin, M.T.D.; Schultz, T.W.; Madden, J.C. An evaluation of global QSAR models for the prediction of the toxicity of phenols to Tetrahymena pyriformis. Chemosphere 2008, 71, 7, 1225–1232.

Published: Iiris Kahn (2014-11-30)

Abstract: This study presents an analysis of the ability of a two-parameter response surface, a multiple linear regression and a neural network model to produce global quantitative structure–activity relationships (QSARs) to predict the toxic potency of phenols to Tetrahymena pyriformis. The phenolic toxicity data set analysed is characterised by multiple mechanisms ...

Regression QMRF
Roberts, D. W.; Aptula, A. O.; Patlewicz, G. Mechanistic Applicability Domains for Non-Animal Based Prediction of Toxicological Endpoints. QSAR Analysis of the Schiff Base Applicability Domain for Skin Sensitization. Chem. Res. Toxicol. 2006, 19, 9, 1228–1233.

Published: Iiris Kahn (2014-11-10)

Abstract: Several recent (1999 onward) publications on skin sensitization to aldehydes and ketones, which can sensitize by covalent binding to skin protein via Schiff base formation, present QSARs based on the Taft sigma* parameter to model reactivity and log P to model hydrophobicity. Here, all of the data are reanalyzed together in a stepwise self-consistent way using ...

HumanHealth Regression QMRF
Papa, E.; Villa, F.; Gramatica, P. Statistically Validated QSARs, Based on Theoretical Descriptors, for Modeling Aquatic Toxicity of Organic Chemicals in Pimephales promelas (Fathead Minnow). J. Chem. Inf. Model. 2005, 45, 5, 1256–1266.

Published: Iiris Kahn (2014-04-08)

Abstract: The use of Quantitative Structure?Activity Relationships in assessing the potential negative effects of chemicals plays an important role in ecotoxicology. (LC50)96h in Pimephales promelas (Duluth database) is widely modeled as an aquatic toxicity end-point. The object of this study was to compare different molecular descriptors in the development of new ...

EcoTox Regression QMRF
Gramatica, P.; Papa, E. Screening and Ranking of POPs for Global Half-Life: QSAR Approaches for Prioritization Based on Molecular Structure. Environ. Sci. Technol. 2007, 41, 8, 2833–2839.

Published: Iiris Kahn (2014-04-07)

Abstract: Persistence in the environment is an important criterion in prioritizing hazardous chemicals and in identifying new persistent organic pollutants (POPs). Degradation half-life in various compartments is among the more commonly used criteria for studying environmental persistence, but the limited availability of experimental data or reliable estimates is a ...

Regression QMRF
Gramatica, P.; Papa, E. An Update of the BCF QSAR Model Based on Theoretical Molecular Descriptors. QSAR Comb. Sci. 2005, 24, 8, 935–960.

Published: Iiris Kahn (2014-02-27)

Abstract: An inspection of an already developed QSAR model is necessary to verify the reproducibility of the model itself, and its present applicability to new chemicals, if a version of calculation software for theoretical molecular descriptors is updated. A QSAR model for bioconcentration in fish, published by the authors and based on 5 molecular descriptors of different ...

EnvironFate Regression QMRF
Ellison, C.M.; Cronin, M.T.D.; Madden, J.C.; Schultz, T.W. Definition of the structural domain of the baseline non-polar narcosis model for Tetrahymena pyriformis. SAR QSAR Environ. Res. 2008, 19, 7-8, 751–783.

Published: Villu Ruusmann, Geven Piir (2012-05-23)

Abstract: The aim of this work was to develop a high-quality 1-octanol/water partition coefficient-dependent (log P) baseline quantitative structure-activity relationship (QSAR) for the toxicity (log IGC(50)(-1)) of classic non-polar narcotics to Tetrahymena pyriformis, and subsequently use this model to define the domain of applicability for baseline narcosis. The ...

Regression QMRF

Showing items 21-28 of 28

Search

Chemical search

Advanced Search

Browse

All of QsarDB
Communities & Collections By Submit Date Authors Titles Journals Endpoints Species Descriptor calculation software Modeling software Model type
This Collection
By Submit Date Authors Titles Journals Endpoints Species Descriptor calculation software Modeling software Model type

Recently added

QsarDB Repository

JRC QSAR Model Database models and data: Recent submissions

Search

Browse

All of QsarDB

This Collection

My Account