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BMCBI
2004
79views more  BMCBI 2004»
13 years 4 months ago
A new mixture model approach to analyzing allelic-loss data using Bayes factors
Background: Allelic-loss studies record data on the loss of genetic material in tumor tissue relative to normal tissue at various loci along the genome. As the deletion of a tumor...
Manisha Desai, Mary J. Emond
IDEAL
2005
Springer
13 years 10 months ago
Cluster Analysis of High-Dimensional Data: A Case Study
Abstract. Normal mixture models are often used to cluster continuous data. However, conventional approaches for fitting these models will have problems in producing nonsingular es...
Richard Bean, Geoffrey J. McLachlan
PAMI
2008
145views more  PAMI 2008»
13 years 4 months ago
Latent-Space Variational Bayes
Variational Bayesian Expectation-Maximization (VBEM), an approximate inference method for probabilistic models based on factorizing over latent variables and model parameters, has ...
JaeMo Sung, Zoubin Ghahramani, Sung Yang Bang
DAGM
2010
Springer
13 years 6 months ago
Gaussian Mixture Modeling with Gaussian Process Latent Variable Models
Density modeling is notoriously difficult for high dimensional data. One approach to the problem is to search for a lower dimensional manifold which captures the main characteristi...
Hannes Nickisch, Carl Edward Rasmussen
JCB
2008
159views more  JCB 2008»
13 years 4 months ago
BayesMD: Flexible Biological Modeling for Motif Discovery
We present BayesMD, a Bayesian Motif Discovery model with several new features. Three different types of biological a priori knowledge are built into the framework in a modular fa...
Man-Hung Eric Tang, Anders Krogh, Ole Winther