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» Gene Expression Clustering with Functional Mixture Models
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TMI
2010
182views more  TMI 2010»
14 years 10 months ago
A Bayesian Mixture Approach to Modeling Spatial Activation Patterns in Multisite fMRI Data
Abstract—We propose a probabilistic model for analyzing spatial activation patterns in multiple functional magnetic resonance imaging (fMRI) activation images such as repeated ob...
Seyoung Kim, Padhraic Smyth, Hal S. Stern
MICCAI
2008
Springer
16 years 29 days ago
Discovering Modes of an Image Population through Mixture Modeling
Abstract. We present iCluster, a fast and efficient algorithm that clusters a set of images while co-registering them using a parameterized, nonlinear transformation model. The out...
Mert R. Sabuncu, Serdar K. Balci, Polina Golland
KDD
2003
ACM
133views Data Mining» more  KDD 2003»
16 years 6 days ago
Interactive Analysis of Gene Interactions Using Graphical gaussian model
DNA microarray provides a powerful basis for analysis of gene expression. Data mining methods such as clustering have been widely applied to microarray data to link genes that sho...
Xintao Wu, Yong Ye, Kalpathi R. Subramanian
BMCBI
2008
201views more  BMCBI 2008»
14 years 12 months ago
A copula method for modeling directional dependence of genes
Background: Genes interact with each other as basic building blocks of life, forming a complicated network. The relationship between groups of genes with different functions can b...
Jong-Min Kim, Yoon-Sung Jung, Engin A. Sungur, Kap...
IJON
2006
95views more  IJON 2006»
14 years 11 months ago
Generalized relevance LVQ (GRLVQ) with correlation measures for gene expression analysis
A correlation-based similarity measure is derived for generalized relevance learning vector quantization (GRLVQ). The resulting GRLVQ-C classifier makes Pearson correlation availa...
Marc Strickert, Udo Seiffert, Nese Sreenivasulu, W...