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» Exploring Visualization Methods for Complex Variables
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GPEM
2000
80views more  GPEM 2000»
13 years 5 months ago
Explanatory Analysis of the Metabolome Using Genetic Programming of Simple, Interpretable Rules
Genetic programming, in conjunction with advanced analytical instruments, is a novel tool for the investigation of complex biological systems at the whole-tissue level. In this stu...
Helen E. Johnson, Richard J. Gilbert, Michael K. W...
BMCBI
2005
122views more  BMCBI 2005»
13 years 5 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,...
BMCBI
2007
215views more  BMCBI 2007»
13 years 5 months ago
Learning causal networks from systems biology time course data: an effective model selection procedure for the vector autoregres
Background: Causal networks based on the vector autoregressive (VAR) process are a promising statistical tool for modeling regulatory interactions in a cell. However, learning the...
Rainer Opgen-Rhein, Korbinian Strimmer
TSP
2010
13 years 6 days ago
Distributed sparse linear regression
The Lasso is a popular technique for joint estimation and continuous variable selection, especially well-suited for sparse and possibly under-determined linear regression problems....
Gonzalo Mateos, Juan Andrés Bazerque, Georg...
BMCBI
2007
104views more  BMCBI 2007»
13 years 5 months ago
Joint mapping of genes and conditions via multidimensional unfolding analysis
Background: Microarray compendia profile the expression of genes in a number of experimental conditions. Such data compendia are useful not only to group genes and conditions base...
Katrijn Van Deun, Kathleen Marchal, Willem J. Heis...