Add to ORKGThe Bayesian product partition model in Booth et al. (2007) simultaneously searches for the optimal number of clusters, which is controlled by the tuning parameter in Crowely’s prior, and clusters genes based on temporal changes of gene expressions. We developed MBBC v2.0 to make this method easily available for statisticians and scientists. MBBC v2.0 is built with three free computer language softwares, OX, R, and C++, taking own advantages of each language. Within MBBC, the search algorithm is implemented with OX and resulting graphs are drawn with R. User-friendly graphic interface is built with DEV C++ to run OX and R programs internally. Thus, MBBC users aren’t required to know how to use OX, R, or DEV C++. However, OX and R must be pr...
International audienceObjective: Data clustering is a common exploration step in the omics era, nota...
This thesis is concerned with the study of a Bayesian clustering algorithm, proposed by Heard et al....
Motivation: Over the last decade, a large variety of clustering algorithms have been developed to de...
Thesis (Ph.D.)--University of Rochester. School of Medicine & Dentistry. Dept. of Biostatistics & Co...
This chapter presents a Bayesian method for model-based clustering of gene expression dynamics and a...
Clustering methods are popular screening tools for microarray data in order to identify subgroups of...
This is the publisher’s final pdf. The published article is copyrighted by American Statistical Asso...
Clustering analysis is an important tool in studying gene expression data. The Bayesian hierarchical...
We live in an era of abundant data. This has necessitated the development of new and innovative stat...
This article establishes a general formulation for Bayesian model-based clustering, in which subset ...
<p>For this purpose, the program was run without population information under the admixture model (i...
<p>a) Summary bar plot of STRUCTURE run at K = 2 showing population assignments for each individual ...
Description We proposed a new model-based clustering method, called the clustering of regression mod...
<p>Clustering methods are designed to separate heterogeneous data into groups of similar objects suc...
Includes bibliographical references (pages 30-31).As the role of large scale data analysis continues...
International audienceObjective: Data clustering is a common exploration step in the omics era, nota...
This thesis is concerned with the study of a Bayesian clustering algorithm, proposed by Heard et al....
Motivation: Over the last decade, a large variety of clustering algorithms have been developed to de...
Thesis (Ph.D.)--University of Rochester. School of Medicine & Dentistry. Dept. of Biostatistics & Co...
This chapter presents a Bayesian method for model-based clustering of gene expression dynamics and a...
Clustering methods are popular screening tools for microarray data in order to identify subgroups of...
This is the publisher’s final pdf. The published article is copyrighted by American Statistical Asso...
Clustering analysis is an important tool in studying gene expression data. The Bayesian hierarchical...
We live in an era of abundant data. This has necessitated the development of new and innovative stat...
This article establishes a general formulation for Bayesian model-based clustering, in which subset ...
<p>For this purpose, the program was run without population information under the admixture model (i...
<p>a) Summary bar plot of STRUCTURE run at K = 2 showing population assignments for each individual ...
Description We proposed a new model-based clustering method, called the clustering of regression mod...
<p>Clustering methods are designed to separate heterogeneous data into groups of similar objects suc...
Includes bibliographical references (pages 30-31).As the role of large scale data analysis continues...
International audienceObjective: Data clustering is a common exploration step in the omics era, nota...
This thesis is concerned with the study of a Bayesian clustering algorithm, proposed by Heard et al....
Motivation: Over the last decade, a large variety of clustering algorithms have been developed to de...