Results 201 to 210 of about 3,379 (242)
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Analysis and refinement of the targeted QSPR method
Computers & Chemical Engineering, 2008Abstract The targeted quantitative structure–property relationship (TQSPR) method of Brauner et al. [Brauner, N., Stateva, R. P., Cholakov, G. St., & Shacham, M. (2006). A structurally “targeted” QSPR method for property prediction. Industrial & Engineering Chemistry Research, 45, 8430–8437] is analyzed in this study with respect to its various ...
Olaf Kahrs +5 more
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QSPR analysis of fluorophilicity for organic compounds
Journal of Fluorine Chemistry, 2007Abstract We constructed a QSPR model from 116 organic compounds for the prediction of fluorophilicity. The 1268 theoretical descriptors explored by means of linear regressions, encoding different aspects of the topological, geometrical, and electronic molecular structure, lead to an optimal seven-parameter equation with a correlation coefficient R ...
Andrew G. Mercader +4 more
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Rank-based ant system method for non-linear QSPR analysis: QSPR studies of the solubility parameter
SAR and QSAR in Environmental Research, 2012The solubility parameter (δ) plays a unique role in the development of stable pharmaceutical formulations for assessing phase segregation during product synthesis. Understanding this parameter helps to determine how a drug substance will behave when processed or when dosed in vivo. The aim of this work was to develop a novel comprehensive yet rapid and
M, Bagheri, A, Golbraikh
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QSPR Analysis of Boiling Point of Chemical Compounds
2002A selected data mining methods have been developed to model the relationships between the structure of organic compounds and their properties. Molecular graph descriptors represent valuable structural descriptors that can be used with success in developing QSPR model. In this study we have used: four valance molecular connectivity indices (1χv, 2χv,3χv,
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Global Performance and Trend of QSAR/QSPR Research: A Bibliometric Analysis
Molecular Informatics, 2014AbstractA bibliometric analysis based on the Science Citation Index Expanded was conducted to provide insights into the publication performance and research trend of quantitative structure‐activity relationship (QSAR) and quantitative structure‐property relationship (QSPR) from 1993 to 2012.
Li, Li, Jianxin, Hu, Yuh-Shan, Ho
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QSPR analysis of the toxicity of aromatic compounds to the algae (Scenedesmus obliquus)
Chemosphere, 2007The quantitative structure-property relationship (QSPR) model was developed for the 50% effective inhibition concentration (48h - EC(50)) of 36 selected substituted benzenes for the algae Scenedesmus obliquus by the application of the Characteristic Root Index (CRI) model.
Melek Türker, Saçan +2 more
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QSPR analysis for infinite dilution activity coefficients of organic compounds
Journal of Molecular Modeling, 2005A quantitative structure-property relationship study of the infinite-dilution activity coefficients for a set of 38 organic compounds in ionic liquids such as 1-methyl-3-ethylimidazolium bis((trifluoromethyl)sulfonyl)imide, 1,2-dimethyl-3-ethylimidazolium bis((trifluoromethyl)-sulfonyl)imide, and 4-methyl-N-butylpyridinium tetrafluoroborate. QSPR study
Kaido, Tämm, Peeter, Burk
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A note on QSPR analysis of total Zagreb and total Randić İndices of octanes
2021Topological indices are important tools for QSPR researches. Wiener, Zagreb, and Randic indices are pioneers of topological indices as the most used topological indices in view of chemistry and chemical graph theory. These three topological indices have been used for modeling physical properties of octanes and other chemical molecules.
Cancan, Murat +5 more
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An Epistemological Analysis of QSPR/QSAR Models
2011Computer sciences have deeply changed the way by which we make science or produce knowledge. With the era of computers and the development of computer science, quantum chemists were among the first scientists to explore the potentialities of the new tool, and even to collaborate in its development.
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QSPR studies of PCBs by the combination of genetic algorithms and PLS analysis
Computers & Chemistry, 2001A hybrid approach that combines genetic algorithms (GA) with PLS analysis is proposed, and a modified cross-validation correlation coefficient (MCVR2) is used as fitness function. The method is applied to QSPR studies of PCBs, in comparison with class regression, and many better models are obtained for each property studied.
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