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Quantitative structure–activity relationship
Known as:
QSAR paradox
, Quantitative structure-property relationship
, QSPR
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Quantitative structure–activity relationship models (QSAR models) are regression or classification models used in the chemical and biological…
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Related topics
Related topics
35 relations
Applicability domain
Chemometrics
Combinatorial chemistry
Convex hull
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Broader (3)
Cheminformatics
Computational chemistry
Medicinal chemistry
Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2016
Highly Cited
2016
Cancer Risk Prediction and Assessment in Human Cells under Synchrotron Radiations Using Quantitative Structure Activity Relationship (QSAR) and Quantitative Structure Properties Relationship (QSPR…
A. Heidari
2016
Corpus ID: 100576872
Editorial: In the present editorial, Quantitative Structure Activity Relationship (QSAR) and Quantitative Structure Properties…
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Highly Cited
2012
Highly Cited
2012
QSAR on aryl-piperazine derivatives with activity on malaria
E. Ibezim
,
P. Duchowicz
,
E. V. Ortiz
,
E. Castro
2012
Corpus ID: 49576329
2004
2004
Use of the DIPPR Database for Development of Quantitative Structure-Property Relationship Correlations: Heat Capacity of Solid Organic Compounds †
B. Goodman
,
W. Wilding
,
J. L. Oscarson
,
R. L. Rowley
2004
Corpus ID: 53331633
Two group-contribution methods have been developed to estimate heat capacities of organic solids at ambient pressure. The power…
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2003
2003
Introduction of Extended Topochemical Atom (ETA) Indices in the Valence Electron Mobile (VEM) Environment as Tools for QSAR/QSPR Studies #
BioChem Press
,
K. Roy
,
G. Ghosh
2003
Corpus ID: 100005963
In order to accomplish further refinement over the TAU formalism in the valence electron mobile (VEM) environment, some of the…
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Review
2002
Review
2002
Fragmental Methods in the Design of New Compounds. Applications of The Advanced Algorithm Builder
P. Japertas
,
R. Didziapetris
,
A. Petrauskas
2002
Corpus ID: 56457124
Fragmental methods (FMs) have great potential in many practical areas related to the design of new lead compounds. Advanced…
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Highly Cited
1999
Highly Cited
1999
A New Efficient Approach for Variable Selection Based on Multiregression: Prediction of Gas Chromatographic Retention Times and Response Factors
Bono Lui
,
N. Trinajstic
,
S. Sild
,
M. Karelson
,
A. Katritzky
Journal of chemical information and computer…
1999
Corpus ID: 15112640
The selection of the most relevant variable is a frequent problem in the analysis of chemical data, especially now considering…
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Highly Cited
1999
Highly Cited
1999
Development and Validation of a Novel Variable Selection Technique with Application to Multidimensional Quantitative Structure-Activity Relationship Studies
C. Waller
,
M. Bradley
Journal of chemical information and computer…
1999
Corpus ID: 206888477
Variable selection is typically a time-consuming and ambiguous procedure in performing quantitative structure−activity…
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Highly Cited
1998
Highly Cited
1998
Design of Topological Indices. Part 10.1 Parameters Based on Electronegativity and Covalent Radius for the Computation of Molecular Graph Descriptors for Heteroatom-Containing Molecules
O. Ivanciuc
,
T. Ivanciuc
,
A. Balaban
Journal of chemical information and computer…
1998
Corpus ID: 10687438
Two new approaches are presented for the calculation of atom and bond parameters for heteroatom-containing molecules used in…
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Highly Cited
1996
Highly Cited
1996
Prediction of Aqueous Solubility for a Diverse Set of Heteroatom-Containing Organic Compounds Using a Quantitative Structure-Property Relationship
J. Sutter
,
P. Jurs
Journal of chemical information and computer…
1996
Corpus ID: 33252092
The primary goal of a quantitative structure−property relationship (QSPR) is to identify a set of structurally based numerical…
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Highly Cited
1986
Highly Cited
1986
Molecular Connectivity in Structure-Activity Analysis
L. Kier
,
Lowell H. Hall
,
Lemont B. Lemont Burwell
1986
Corpus ID: 94631384
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