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Ranking of QSAR models to predict minimal inhibitory concentrations toward Mycobacterium tuberculosis for a set of fluoroquinolonesVračko, Marjan ; Minovski, Nikola ; Héberger, KárolyCP-ANN technique was used to build 54 different QSAR models. The models were built for three sets (assays) of fluoroquinolones considering their antituberculosis activity and using different ... technical parameters (dimension of network and number of learning epochs). The models served as a reliable basis for ranking by a new powerful method based on sum of ranking differences (SRD). With the applied SRD procedure we can find the optimal ones. The best model can be selected easily for the first assay. Two models can be recommended for the second assay, and no recommended model was found for the assay3.Source: Acta chimica slovenica. - ISSN 1318-0207 (Vol. 57, no. 3, 2010, str. 586-590)Type of material - article, component partPublish date - 2010Language - englishCOBISS.SI-ID - 4510490
Author
Vračko, Marjan |
Minovski, Nikola |
Héberger, Károly
Topics
QSAR |
modeling |
ranking |
method comparison |
neural networks |
prediction of antituberculosis activity
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Database name | Field | Year |
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Links to authors' personal bibliographies | Links to information on researchers in the SICRIS system |
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Vračko, Marjan | 15991 |
Minovski, Nikola | 29497 |
Héberger, Károly | ![]() |
Source: Personal bibliographies
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