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» Exploring Visualization Methods for Complex Variables
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GPEM
2000
80views more  GPEM 2000»
14 years 11 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»
14 years 11 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»
14 years 11 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
14 years 6 months 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...
90
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BMCBI
2007
104views more  BMCBI 2007»
14 years 11 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...