Results 161 to 170 of about 11,478 (188)
Some of the next articles are maybe not open access.
International Journal of Quantitative Structure-Property Relationships, 2020
Predictive modeling of the properties of polymers and polymeric materials is getting more attention, while it is still very complicated due to complexity of these materials. In this review, we discuss main applications of quantitative structure-property/activity relationships (QSPR/QSAR) methods for polymers published recently.
Bakhtiyor Rasulev +1 more
openaire +1 more source
Predictive modeling of the properties of polymers and polymeric materials is getting more attention, while it is still very complicated due to complexity of these materials. In this review, we discuss main applications of quantitative structure-property/activity relationships (QSPR/QSAR) methods for polymers published recently.
Bakhtiyor Rasulev +1 more
openaire +1 more source
Journal of Chemical Information and Computer Sciences, 2001
A quantitative structure property relationship study of the flash point of a diverse set of 271 compounds provided a general three-parameter QSPR model (R(2) = 0.9020, R(2)(cv) = 0.8985, s = 16.1). Use of the experimental boiling point as a descriptor gives a three-descriptor equation with R(2) = 0.9529.
A R, Katritzky +3 more
openaire +2 more sources
A quantitative structure property relationship study of the flash point of a diverse set of 271 compounds provided a general three-parameter QSPR model (R(2) = 0.9020, R(2)(cv) = 0.8985, s = 16.1). Use of the experimental boiling point as a descriptor gives a three-descriptor equation with R(2) = 0.9529.
A R, Katritzky +3 more
openaire +2 more sources
Automated QSPR through Competitive Workflow
Journal of Computer-Aided Molecular Design, 2005This paper describes a novel software architecture, Competitive Workflow, which implements workflow as a distributed and competitive multi-agent system. The implementation of a competitive workflow architecture designed to model important computer-aided molecular design workflows, the Discovery Bus, is described.
Leahy DE +4 more
openaire +3 more sources
Journal of Computational Chemistry, 2008
AbstractClassical quantitative structure‐properties relationship (QSPR) statistical techniques unavoidably present an inherent paradoxical computational context. They rely on the definition of a Gram matrix in descriptor spaces, which is used afterwards to reduce the original dimension via several possible kinds of algebraic manipulations.
Ramon, Carbó-Dorca +2 more
openaire +2 more sources
AbstractClassical quantitative structure‐properties relationship (QSPR) statistical techniques unavoidably present an inherent paradoxical computational context. They rely on the definition of a Gram matrix in descriptor spaces, which is used afterwards to reduce the original dimension via several possible kinds of algebraic manipulations.
Ramon, Carbó-Dorca +2 more
openaire +2 more sources
QSPR modeling of UV absorption intensities
Journal of Computer-Aided Molecular Design, 2007Literature UV absorption intensities at 260 nm and 25 degrees C in water of a diverse set of 805 organic compounds when analyzed by CODESSA Pro software using an initial pool of 800 + descriptors provide a significant QSPR correlation (R (2) = 0.692). Concurrently, a neural networks approach was used to develop a corresponding nonlinear model.
Alan R, Katritzky +3 more
openaire +2 more sources
2015
QSAR/QSPR analysis started with different classical approaches constituting the core concept of predictive modeling analysis in the context of structure–activity relationships. Such classical techniques have been based on various postulates and hypotheses.
Kunal Roy +2 more
openaire +1 more source
QSAR/QSPR analysis started with different classical approaches constituting the core concept of predictive modeling analysis in the context of structure–activity relationships. Such classical techniques have been based on various postulates and hypotheses.
Kunal Roy +2 more
openaire +1 more source
Conformation-Dependent QSPR Models: logPOW
Journal of Chemical Information and Modeling, 2011Quantitative structure-property relationships for predicting the water-octanol partition coefficient, logP(OW), are reported. The models are based on local properties calculated at the standard isodensity surface using semiempirical molecular orbital theory and use descriptors obtained as the areas of the surface found in each bin in a predefined ...
Muehlbacher, M. +4 more
openaire +3 more sources
Multimolecular polyhedra and QSPR
Journal of Mathematical Chemistry, 2014zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +1 more source
Journal of Dispersion Science and Technology, 2007
A quantitative structure property relationship; QSPR was preformed as a means to predict critical micelle concentration of nonionic surfactants via correlating properties to parameters calculated from molecular structure. Such parameters; molecular weight, M w , hydrophobic‐hydrophilic fragments molecular weight ratio, χ, polarizability, α, partition ...
openaire +1 more source
A quantitative structure property relationship; QSPR was preformed as a means to predict critical micelle concentration of nonionic surfactants via correlating properties to parameters calculated from molecular structure. Such parameters; molecular weight, M w , hydrophobic‐hydrophilic fragments molecular weight ratio, χ, polarizability, α, partition ...
openaire +1 more source
QSPR i QSAR supstituiranih ftalimida
1999U ovome radu provedena su QSPR i QSAR istraživanja nekoliko nizova supstituiranih ftalimida, od kojih je većina pripremljena na našem fakultetu.Koristeći topologijske indekse i razne fizičko-kemijske parametre kao parametre aktivnosti dobiveni su značajni QSPR iQSAR modeli koji predviđaju aktivnost nekih novih ftalimida.
openaire +3 more sources