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» Designing Neural Networks Using Gene Expression Programming
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IJCNN
2008
IEEE
14 years 2 months ago
Dataset complexity can help to generate accurate ensembles of k-nearest neighbors
— Gene expression based cancer classification using classifier ensembles is the main focus of this work. A new ensemble method is proposed that combines predictions of a small ...
Oleg Okun, Giorgio Valentini
EVOW
2003
Springer
14 years 1 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...
BMCBI
2011
13 years 2 months ago
Using Stochastic Causal Trees to Augment Bayesian Networks for Modeling eQTL Datasets
Background: The combination of genotypic and genome-wide expression data arising from segregating populations offers an unprecedented opportunity to model and dissect complex phen...
Kyle C. Chipman, Ambuj K. Singh
BMCBI
2007
148views more  BMCBI 2007»
13 years 7 months ago
fREDUCE: Detection of degenerate regulatory elements using correlation with expression
Background: The precision of transcriptional regulation is made possible by the specificity of physical interactions between transcription factors and their cognate binding sites ...
Randy Z. Wu, Christina Chaivorapol, Jiashun Zheng,...
ICONIP
2010
13 years 5 months ago
Exploring Features and Classifiers to Classify MicroRNA Expression Profiles of Human Cancer
Recently, some non-coding small RNAs, known as microRNAs (miRNA), have drawn a lot of attention to identify their role in gene regulation and various biological processes. The miRN...
Kyung-Joong Kim, Sung-Bae Cho