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Mendeley readers
Chapter title |
Prediction of Biochemical Endpoints by the CORAL Software: Prejudices, Paradoxes, and Results
|
---|---|
Chapter number | 27 |
Book title |
Computational Toxicology
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Published in |
Methods in molecular biology, January 2018
|
DOI | 10.1007/978-1-4939-7899-1_27 |
Pubmed ID | |
Book ISBNs |
978-1-4939-7898-4, 978-1-4939-7899-1
|
Authors |
Andrey A. Toropov, Alla P. Toropova, Alessandra Roncaglioni, Emilio Benfenati, Toropov, Andrey A., Toropova, Alla P., Roncaglioni, Alessandra, Benfenati, Emilio |
Abstract |
Quantitative structure-activity relationships (QSARs) for prediction of toxicological endpoints built up with the CORAL software are discussed. Prejudices related to these QSAR models are listed. Possible ways to improve the software are discussed. |
Mendeley readers
The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 4 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Bachelor | 1 | 25% |
Researcher | 1 | 25% |
Student > Postgraduate | 1 | 25% |
Student > Master | 1 | 25% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 1 | 25% |
Psychology | 1 | 25% |
Chemistry | 1 | 25% |
Unknown | 1 | 25% |