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In this study, a robust and highly predictive group-based QSAR (GQSAR) model has been developed based on the descriptors calculated for the fragments of 20 1,4-dihydropyridine (DHP) derivatives.
In both cases, selection was based on the descriptors of the compounds of the training set.
This framework is based on the descriptors decomposition in three levels: primitive extraction, primitive coding and code aggregation.
Mixture descriptors developed in this study were constructed as suggested in previous work [3, 6], based on the descriptors of individual components of the mixture.
First, we constructed a questionnaire based on the descriptors collected from various sources in order to elicit university teachers' views on the importance of these descriptors.
A population of 100 rigorously validated linear QSAR models were established based on the descriptors calculated in DRAGON program and selected by genetic algorithm (GA).
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The current configurations are detected using an observer based on the descriptor system theory.
Based on the descriptor system model, a fault estimation filter which can simultaneously estimate the state and the sensor fault magnitudes is designed via a minimum-variance principle.
The delay-dependent decentralized stabilization problem of multi-channel singular time-delay time-invariant systems subject to multiple internal and external incommensurate constant point delays is discussed based on the descriptor integral-inequality approach.
For carcinogenicity endpoint, as for the models developed for the other endpoints, CAESAR implemented a tool for the general evaluation of the AD based on the descriptor range for the dataset; therefore, predicted values for chemicals outside the descriptor range can be judged as less reliable.
cor.res: correlation R based on the votes for each protein sequence in the dataset; cor.des: correlation R based on the descriptor values for the 20 amino acids.
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based on the qualifications
based on the specifications
based on the characterizations
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