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 SM ISO690:2012TINKOV, Oleg, POLISHCHUK, Pavel, GRIGOREV, Veniamin, POROZOV, Yuri. The Cross-Interpretation of QSAR Toxicological Models. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 1-4 decembrie 2020, Moscova. Switzerland: Springer Nature Switzerland AG, 2020, Special Issue, pp. 262-273. ISBN 978-303057820-6. ISSN 03029743. DOI: https://doi.org/10.1007/978-3-030-57821-3_23 |
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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Special Issue, 2020 |
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Simpozionul "Symposium on Bioinformatics Research and Applications" Moscova, Rusia, 1-4 decembrie 2020 | |
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| DOI:https://doi.org/10.1007/978-3-030-57821-3_23 | |
| Pag. 262-273 | |
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The investigation of influence of the molecular structure of different organic compounds on acute, developmental toxicity, mutagenicity has been carried out with the usage of 2D simplex representation of molecular structure and Support Vector Machine (SVM), Random Forest (RF), Gradient Boosting Machine (GBM), Partial Least Squares (PLS). Suitable QSAR (Quantitative Structure - Activity Relationships) models were obtained. The study was focused on QSAR model interpretation. The aim of the study was to develop a set of structural fragments that steadily increase various types of toxicity. The interpretation allowed to detail the molecular environment of known toxicophors and to propose new fragments. |
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