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» Bayesian Networks Learning for Gene Expression Datasets
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EVOW
2008
Springer
15 years 1 months ago
Learning Gaussian Graphical Models of Gene Networks with False Discovery Rate Control
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...
Jose M. Peña
CEC
2007
IEEE
15 years 3 months ago
Evolving hypernetwork classifiers for microRNA expression profile analysis
Abstract-- High-throughput microarrays inform us on different outlooks of the molecular mechanisms underlying the function of cells and organisms. While computational analysis for ...
Sun Kim, Soo-Jin Kim, Byoung-Tak Zhang
ML
2010
ACM
151views Machine Learning» more  ML 2010»
14 years 10 months ago
Inductive transfer for learning Bayesian networks
In several domains it is common to have data from different, but closely related problems. For instance, in manufacturing, many products follow the same industrial process but with...
Roger Luis, Luis Enrique Sucar, Eduardo F. Morales
BMCBI
2010
229views more  BMCBI 2010»
14 years 12 months ago
Mocapy++ - A toolkit for inference and learning in dynamic Bayesian networks
Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distribut...
Martin Paluszewski, Thomas Hamelryck
BMCBI
2007
148views more  BMCBI 2007»
14 years 12 months ago
Evaluation of gene-expression clustering via mutual information distance measure
Background: The definition of a distance measure plays a key role in the evaluation of different clustering solutions of gene expression profiles. In this empirical study we compa...
Ido Priness, Oded Maimon, Irad E. Ben-Gal