Add to ORKGGenetic programming (GP) based data fusion and AdaBoost can both improve in vitro prediction of Cytochrome P450 activity by combining artificial neural networks (ANN). Pharmaceutical drug design data provided by high throughput screening (HTS) is used to train many base ANN classifiers. In data mining (KDD) we must avoid over fitting
Artificial Neural Network for Drug Design, Delivery and Disposition provides an in-depth look at the...
Cancer is a disease induced by the abnormal growth of cells in body tissues. This disease is commonl...
Identifying potential and druggable targets for developing new drugs is the first major step for cur...
Genetic programming (GP) based data fusion and AdaBoost can both improve in vitro prediction of Cyto...
Genetic programming (GP) offers a generic method of automatically fusing together classifiers using ...
We have previously shown on a range of benchmarks [ Langdon and Buxton, 2001b] genetic programming ...
Genetic programming (GP) is used to extract from rat oral bioavailability (OB) measurements simple,...
Artificial Neural Networks (ANNs) are trained using High Throughput Screening (HTS) data to recover ...
Several machine learning techniques were evaluated for the prediction of parameters relevant in phar...
[[abstract]]Machine learning is a well-known approach for virtual screening. Recently, deep learning...
In silico screening of chemical libraries or virtual chemicals may reduce drug discovery and medicin...
A major cause of failed drug discovery programs is suboptimal target selection, resulting in the dev...
Caballero, J (Caballero, Julio). Univ Talca, Ctr Bioinformat & Simulac Mol, Talca, ChileMany article...
Perturbed bioprocesses were predicted using both CG-TARGET and a method that calculated enrichment o...
Following the explosive growth in chemical and biological data, the shift from traditional methods o...
Artificial Neural Network for Drug Design, Delivery and Disposition provides an in-depth look at the...
Cancer is a disease induced by the abnormal growth of cells in body tissues. This disease is commonl...
Identifying potential and druggable targets for developing new drugs is the first major step for cur...
Genetic programming (GP) based data fusion and AdaBoost can both improve in vitro prediction of Cyto...
Genetic programming (GP) offers a generic method of automatically fusing together classifiers using ...
We have previously shown on a range of benchmarks [ Langdon and Buxton, 2001b] genetic programming ...
Genetic programming (GP) is used to extract from rat oral bioavailability (OB) measurements simple,...
Artificial Neural Networks (ANNs) are trained using High Throughput Screening (HTS) data to recover ...
Several machine learning techniques were evaluated for the prediction of parameters relevant in phar...
[[abstract]]Machine learning is a well-known approach for virtual screening. Recently, deep learning...
In silico screening of chemical libraries or virtual chemicals may reduce drug discovery and medicin...
A major cause of failed drug discovery programs is suboptimal target selection, resulting in the dev...
Caballero, J (Caballero, Julio). Univ Talca, Ctr Bioinformat & Simulac Mol, Talca, ChileMany article...
Perturbed bioprocesses were predicted using both CG-TARGET and a method that calculated enrichment o...
Following the explosive growth in chemical and biological data, the shift from traditional methods o...
Artificial Neural Network for Drug Design, Delivery and Disposition provides an in-depth look at the...
Cancer is a disease induced by the abnormal growth of cells in body tissues. This disease is commonl...
Identifying potential and druggable targets for developing new drugs is the first major step for cur...