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» Ensemble of Linear Models for Predicting Drug Properties
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JCISD
2006
114views more  JCISD 2006»
13 years 4 months ago
Ensemble of Linear Models for Predicting Drug Properties
We propose a new classification method for prediction of drug properties, called the Random Feature Subset Boosting for Linear Discriminant Analysis (LDA). The main novelty of this...
Tomasz Arodz, David A. Yuen, Arkadiusz Z. Dudek
BMCBI
2007
107views more  BMCBI 2007»
13 years 4 months ago
Prediction of potential drug targets based on simple sequence properties
Background: During the past decades, research and development in drug discovery have attracted much attention and efforts. However, only 324 drug targets are known for clinical dr...
Qingliang Li, Luhua Lai
EVOW
2003
Springer
13 years 10 months ago
Comparison of AdaBoost and Genetic Programming for Combining Neural Networks for Drug Discovery
Genetic programming (GP) based data fusion and AdaBoost can both improve in vitro prediction of Cytochrome P450 activity by combining artificial neural networks (ANN). Pharmaceuti...
William B. Langdon, S. J. Barrett, Bernard F. Buxt...
COMPLIFE
2006
Springer
13 years 8 months ago
Adaptive Approach for Modelling Variability in Pharmacokinetics
Abstract. We present an improved adaptive approach for studying systems of ODEs affected by parameter variability and state space uncertainty. Our approach is based on a reformulat...
Andrea Y. Weiße, Illia Horenko, Wilhelm Huis...
BMCBI
2010
117views more  BMCBI 2010»
13 years 4 months ago
Properties and identification of antibiotic drug targets
Background: We analysed 48 non-redundant antibiotic target proteins from all bacteria, 22 antibiotic target proteins from E. coli only and 4243 non-drug targets from E. coli to id...
Tala Bakheet, Andrew J. Doig