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RECOMB
2003
Springer
14 years 8 months ago
Physical network models and multi-source data integration
We develop a new framework for inferring models of transcriptional regulation. The models in this approach, which we call physical models, are constructed on the basis of verifiab...
Chen-Hsiang Yeang, Tommi Jaakkola
BMCBI
2005
122views more  BMCBI 2005»
13 years 8 months ago
FACT - a framework for the functional interpretation of high-throughput experiments
Background: Interpreting the results of high-throughput experiments, such as those obtained from DNA-microarrays, is an often time-consuming task due to the high number of data-po...
Felix Kokocinski, Nicolas Delhomme, Gunnar Wrobel,...
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
BMCBI
2010
152views more  BMCBI 2010»
13 years 8 months ago
Comparative study of three commonly used continuous deterministic methods for modeling gene regulation networks
Background: A gene-regulatory network (GRN) refers to DNA segments that interact through their RNA and protein products and thereby govern the rates at which genes are transcribed...
Martin T. Swain, Johannes J. Mandel, Werner Dubitz...
BMCBI
2011
13 years 3 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