Quantitative Structure-Activity Relationship
"Quantitative Structure-Activity Relationship" is a descriptor in the National Library of Medicine's controlled vocabulary thesaurus,
MeSH (Medical Subject Headings). Descriptors are arranged in a hierarchical structure,
which enables searching at various levels of specificity.
A quantitative prediction of the biological, ecotoxicological or pharmaceutical activity of a molecule. It is based upon structure and activity information gathered from a series of similar compounds.
Descriptor ID |
D021281
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MeSH Number(s) |
G02.111.830.500 G07.690.773.997.500
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Concept/Terms |
Quantitative Structure-Activity Relationship- Quantitative Structure-Activity Relationship
- Quantitative Structure Activity Relationship
- Quantitative Structure-Activity Relationships
- Relationship, Quantitative Structure-Activity
- Relationships, Quantitative Structure-Activity
- Structure-Activity Relationship, Quantitative
- Structure-Activity Relationships, Quantitative
- Structure Activity Relationship, Quantitative
- QSAR
|
Below are MeSH descriptors whose meaning is more general than "Quantitative Structure-Activity Relationship".
Below are MeSH descriptors whose meaning is more specific than "Quantitative Structure-Activity Relationship".
This graph shows the total number of publications written about "Quantitative Structure-Activity Relationship" by people in this website by year, and whether "Quantitative Structure-Activity Relationship" was a major or minor topic of these publications.
To see the data from this visualization as text,
click here.
Year | Major Topic | Minor Topic | Total |
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2003 | 0 | 1 | 1 |
2005 | 1 | 0 | 1 |
2006 | 1 | 0 | 1 |
2007 | 2 | 2 | 4 |
2008 | 3 | 2 | 5 |
2009 | 1 | 4 | 5 |
2010 | 5 | 2 | 7 |
2011 | 4 | 2 | 6 |
2012 | 4 | 4 | 8 |
2013 | 6 | 1 | 7 |
2014 | 5 | 4 | 9 |
2015 | 1 | 3 | 4 |
2016 | 4 | 1 | 5 |
2017 | 1 | 4 | 5 |
2018 | 3 | 6 | 9 |
2019 | 1 | 5 | 6 |
2020 | 1 | 0 | 1 |
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Below are the most recent publications written about "Quantitative Structure-Activity Relationship" by people in Profiles.
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Kar S, Leszczynski J. Is intraspecies QSTR model answer to toxicity data gap filling: Ecotoxicity modeling of chemicals to avian species. Sci Total Environ. 2020 Oct 10; 738:139858.
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Sizochenko N, Syzochenko M, Fjodorova N, Rasulev B, Leszczynski J. Evaluating genotoxicity of metal oxide nanoparticles: Application of advanced supervised and unsupervised machine learning techniques. Ecotoxicol Environ Saf. 2019 Dec 15; 185:109733.
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Toropov AA, Toropova AP, Leszczynska D, Leszczynski J. "Ideal correlations" for biological activity of peptides. Biosystems. 2019 Jul; 181:51-57.
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Foroozesh M, Sridhar J, Goyal N, Liu J. Coumarins and P450s, Studies Reported to-Date. Molecules. 2019 Apr 24; 24(8).
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Petrosyan LS, Sizochenko N, Leszczynski J, Rasulev B. Modeling of Glass Transition Temperatures for Polymeric Coating Materials: Application of QSPR Mixture-based Approach. Mol Inform. 2019 08; 38(8-9):e1800150.
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Toropova AP, Toropov AA, Benfenati E, Leszczynska D, Leszczynski J. Virtual Screening of Anti-Cancer Compounds: Application of Monte Carlo Technique. Anticancer Agents Med Chem. 2019; 19(2):148-153.
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Samanta PN, Kar S, Leszczynski J. Recent Advances of In-Silico Modeling of Potent Antagonists for the Adenosine Receptors. Curr Pharm Des. 2019; 25(7):750-773.
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Khan K, Kar S, Sanderson H, Roy K, Leszczynski J. Ecotoxicological Modeling, Ranking and Prioritization of Pharmaceuticals Using QSTR and i-QSTTR Approaches: Application of 2D and Fragment Based Descriptors. Mol Inform. 2019 08; 38(8-9):e1800078.
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Jean J, Kar S, Leszczynski J. QSAR modeling of adipose/blood partition coefficients of Alcohols, PCBs, PBDEs, PCDDs and PAHs: A data gap filling approach. Environ Int. 2018 12; 121(Pt 2):1193-1203.
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Ojha PK, Kar S, Roy K, Leszczynski J. Toward comprehension of multiple human cells uptake of engineered nano metal oxides: quantitative inter cell line uptake specificity (QICLUS) modeling. Nanotoxicology. 2019 02; 13(1):14-34.