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» Gene Expression Clustering with Functional Mixture Models
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SDM
2004
SIAM
218views Data Mining» more  SDM 2004»
13 years 10 months ago
Mixture Density Mercer Kernels: A Method to Learn Kernels Directly from Data
This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density e...
Ashok N. Srivastava
BIODATAMINING
2008
135views more  BIODATAMINING 2008»
13 years 9 months ago
Fast Gene Ontology based clustering for microarray experiments
Background: Analysis of a microarray experiment often results in a list of hundreds of diseaseassociated genes. In order to suggest common biological processes and functions for t...
Kristian Ovaska, Marko Laakso, Sampsa Hautaniemi
KES
2005
Springer
14 years 2 months ago
Bayesian Validation of Fuzzy Clustering for Analysis of Yeast Cell Cycle Data
Clustering for the analysis of the gene expression profiles has been used for identifying the functions of the genes and of unknown genes. Since the genes usually belong to multipl...
Kyung-Joong Kim, Si-Ho Yoo, Sung-Bae Cho
IPPS
2003
IEEE
14 years 2 months ago
Gene Clustering Using Self-Organizing Maps and Particle Swarm Optimization
Gene clustering, the process of grouping related genes in the same cluster, is at the foundation of different genomic studies that aim at analyzing the function of genes. Microarr...
Xiang Xiao, Ernst R. Dow, Russell C. Eberhart, Zin...
KDD
2006
ACM
156views Data Mining» more  KDD 2006»
14 years 9 months ago
Discovering significant OPSM subspace clusters in massive gene expression data
Order-preserving submatrixes (OPSMs) have been accepted as a biologically meaningful subspace cluster model, capturing the general tendency of gene expressions across a subset of ...
Byron J. Gao, Obi L. Griffith, Martin Ester, Steve...