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» Using Bayesian networks to analyze expression data
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JMLR
2010
134views more  JMLR 2010»
14 years 4 months ago
Bayesian Algorithms for Causal Data Mining
We present two Bayesian algorithms CD-B and CD-H for discovering unconfounded cause and effect relationships from observational data without assuming causal sufficiency which prec...
Subramani Mani, Constantin F. Aliferis, Alexander ...
ICA
2007
Springer
15 years 1 months ago
Infinite Sparse Factor Analysis and Infinite Independent Components Analysis
Abstract. A nonparametric Bayesian extension of Independent Components Analysis (ICA) is proposed where observed data Y is modelled as a linear superposition, G, of a potentially i...
David Knowles, Zoubin Ghahramani
76
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CSB
2005
IEEE
124views Bioinformatics» more  CSB 2005»
15 years 3 months ago
Identifying Local Gene Expression Patterns in Biomolecular Networks
This study is aimed at elucidating putative transcription regulators (TRs) responsible for the observed differential expression pattern. Combined direct promoter binding and indir...
Andrey Y. Sivachenko, Anton Yuryev, Nikolai Darase...
CIVR
2003
Springer
166views Image Analysis» more  CIVR 2003»
15 years 3 months ago
Evaluation of Expression Recognition Techniques
The most expressive way humans display emotions is through facial expressions. In this work we report on several advances we have made in building a system for classification of f...
Ira Cohen, Nicu Sebe, Yafei Sun, Michael S. Lew, T...
BMCBI
2011
14 years 4 months ago
Multivariate analysis of microarray data: differential expression and differential connection
Background: Typical analysis of microarray data ignores the correlation between gene expression values. In this paper we present a model for microarray data which specifically all...
Harri T. Kiiveri