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» Gene Expression Clustering with Functional Mixture Models
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ICPR
2000
IEEE
16 years 26 days ago
On Gaussian Radial Basis Function Approximations: Interpretation, Extensions, and Learning Strategies
In this paper we focus on an interpretation of Gaussian radial basis functions (GRBF) which motivates extensions and learning strategies. Specifically, we show that GRBF regressio...
Mário A. T. Figueiredo
102
Voted
ICASSP
2010
IEEE
14 years 12 months ago
Hierarchical Gaussian Mixture Model
Gaussian mixture models (GMMs) are a convenient and essential tool for the estimation of probability density functions. Although GMMs are used in many research domains from image ...
Vincent Garcia, Frank Nielsen, Richard Nock
BMCBI
2007
182views more  BMCBI 2007»
14 years 12 months ago
Additive risk survival model with microarray data
Background: Microarray techniques survey gene expressions on a global scale. Extensive biomedical studies have been designed to discover subsets of genes that are associated with ...
Shuangge Ma, Jian Huang
BMCBI
2006
85views more  BMCBI 2006»
14 years 12 months ago
Use of physiological constraints to identify quantitative design principles for gene expression in yeast adaptation to heat shoc
Background: Understanding the relationship between gene expression changes, enzyme activity shifts, and the corresponding physiological adaptive response of organisms to environme...
Ester Vilaprinyó, Rui Alves, Albert Sorriba...
BMCBI
2007
168views more  BMCBI 2007»
14 years 12 months ago
GOSim - an R-package for computation of information theoretic GO similarities between terms and gene products
Background: With the increased availability of high throughput data, such as DNA microarray data, researchers are capable of producing large amounts of biological data. During the...
Holger Fröhlich, Nora Speer, Annemarie Poustk...