Distributions on classifications are met wherever we work with categorical variables. A vast investigation has been done in developing methods for statistical analysis of nominal variables (e.g. variables with simple classification), partially are solved also problems for ordered classifications and classifications with assigned numbers. In this paper we propose a general model which enables us...

In this paper, quantitative–structure–toxicity–relationship (QSTR) models are developed for predicting the toxicity of halogen, sulfur and chlorinated aromatic compounds. Two sets of compounds, containing mainly halogen and sulfur inorganic compounds in the first set and chlorinated aromatic compounds in the second, are investigated for their toxicity level with the aid of the conceptual Densit...

Presently, 151 widely-diverse pyridinylimidazole-based compounds that show inhibitory activities at the TNF-α release were investigated. By using the distance comparison technique (DISCOtech), comparative molecular field analysis (CoMFA), and comparative molecular similarity index analysis (CoMSIA) methods, the pharmacophore models and the three-dimensional quantitative structure-activity relat...

2.1.Date of QMRF: 06.10.2009 2.2.QMRF author(s) and contact details: [1]Indrek Tulp Molcode Ltd. Turu 2, Tartu, 51014, Estonia [email protected] http://www.molcode.com [2]Tarmo Tamm Molcode Ltd. Turu 2, Tartu, 51014, Estonia [email protected] http://www.molcode.com [3]Gunnar Karelson Molcode Ltd. Turu 2, Tartu, 51014, Estonia [email protected] http://www.molcode.com [4]Dimitar Dobchev Molcod...

In this contribution, the advantages and limitations of two computational techniques that can be used for the investigation of nanoparticles activity and toxicity: classic nano-QSAR (Quantitative Structure-Activity Relationships employed for nanomaterials) and 3D nano-QSAR (three-dimensional Quantitative Structure-Activity Relationships, such us Comparative Molecular Field Analysis, CoMFA/Compa...

2.1.Date of QMRF: 17.12.2010 2.2.QMRF author(s) and contact details: [1]Indrek Tulp Molcode Ltd. Turu 2, Tartu, 51014, Estonia [email protected] http://www.molcode.com [2]Tarmo Tamm Molcode Ltd. Turu 2, Tartu, 51014, Estonia [email protected] http://www.molcode.com [3]Gunnar Karelson Molcode Ltd. Turu 2, Tartu, 51014, Estonia [email protected] http://www.molcode.com [4]Dimitar Dobchev Molcod...

March 13, 2013 Type Package Title Calculate the predictive squared correlation coefficient Version 1.1.0 Date 2013-03-13 Author Torsten Thalheim Maintainer Torsten Thalheim Description The external prediction capability of quantitative structure-activity relationship (QSAR) models is often quantified using the predictive squared correlation coefficient. This value can b...

Several new 2-(2-(4-chlorophenyl)acetyl)-N-arylhydrazinecarbothioamides 1, 5-(4-chlorobenzyl)-4-aryl-4H-1,2,4triazole-3-thiols 2, 5-(4-chlorobenzyl)-N-aryl-1,3,4-thiadiazol-2-amines 3 and 5-(4-chlorobenzyl)-N-aryl-1,3,4-oxadiazol-2amines 4 have been synthesized and screened for their antibacterial activity against gram +ve and gram –ve bacteria i.e S.aureus and E. coli. The QSAR studies of thes...

Performance of the E-state descriptors was tested against simple counts of the 35 atom types that the Kier-Hall E-states are based upon, by building PLS models for clogP, aqueous solubility, human intestinal absorption (HIA) and blood brain barrier (BBB). The results indicate that the simple counts work at least as well as E-state descriptors in building models for solubility and BBB, while sur...