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» Gene Expression Clustering with Functional Mixture Models
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ICASSP
2011
IEEE
13 years 24 days ago
Bayesian sensing hidden Markov models for speech recognition
We introduce Bayesian sensing hidden Markov models (BS-HMMs) to represent speech data based on a set of state-dependent basis vectors. By incorporating the prior density of sensin...
George Saon, Jen-Tzung Chien
JCB
2008
159views more  JCB 2008»
13 years 9 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
BMCBI
2008
122views more  BMCBI 2008»
13 years 9 months ago
Reconstructing networks of pathways via significance analysis of their intersections
Background: Significance analysis at single gene level may suffer from the limited number of samples and experimental noise that can severely limit the power of the chosen statist...
Mirko Francesconi, Daniel Remondini, Nicola Nerett...
DIS
2006
Springer
14 years 22 days ago
On Class Visualisation for High Dimensional Data: Exploring Scientific Data Sets
Parametric Embedding (PE) has recently been proposed as a general-purpose algorithm for class visualisation. It takes class posteriors produced by a mixture-based clustering algori...
Ata Kabán, Jianyong Sun, Somak Raychaudhury...
BMCBI
2006
166views more  BMCBI 2006»
13 years 9 months ago
bioNMF: a versatile tool for non-negative matrix factorization in biology
Background: In the Bioinformatics field, a great deal of interest has been given to Non-negative matrix factorization technique (NMF), due to its capability of providing new insig...
Alberto D. Pascual-Montano, Pedro Carmona-Saez, Mo...