6 search results - page 1 / 2 » Learning Gaussian Graphical Models of Gene Networks with Fal... |
EVOW
2008
Springer
13 years 6 months ago
2008
Springer
In many cases what matters is not whether a false discovery is made or not but the expected proportion of false discoveries among all the discoveries made, i.e. the so-called false...
ICASSP
2008
IEEE
13 years 11 months ago
2008
IEEE
Graphical models of brain functional connectivity have matured from con rming a priori hypotheses to an exploratory tool for discovering unknown connectivity. However, exploratory...
BMCBI
2008
13 years 5 months ago
2008
Background: False discovery rate (FDR) methods play an important role in analyzing highdimensional data. There are two types of FDR, tail area-based FDR and local FDR, as well as ...
AAAI
2008
13 years 7 months ago
2008
Modern Bayesian Network learning algorithms are timeefficient, scalable and produce high-quality models; these algorithms feature prominently in decision support model development...
BMCBI
2010
13 years 5 months ago
2010
Background: Novel strategies are required in order to handle the huge amount of data produced by microarray technologies. To infer gene regulatory networks, the first step is to f...