Model-based Bayesian clustering (MBBC)
نویسندگان
چکیده
MOTIVATION The program MBBC 2.0 clusters time-course microarray data using a Bayesian product partition model. RESULTS The Bayesian product partition model in Booth et al. (2007) simultaneously searches for the optimal number of clusters, and assigns cluster memberships based on temporal changes of gene expressions. MBBC 2.0 to makes this method easily available for statisticians and scientists, and is built with three free computer language software packages: Ox, R and C++, taking advantage of the strengths of each language. Within MBBC, the search algorithm is implemented with Ox and resulting graphs are drawn with R. A user-friendly graphical interface is built with C++ to run the Ox and R programs internally. Thus, MBBC users are not required to know how to use Ox, R or C++, but they must be pre-installed. AVAILABILITY A self-extractable zip file, MBBC20zip.exe, is available at the MBBC webpage www.stat.ufl.edu/~casella/mbbc/, which contains MBBC.exe, source files, and all other related files. The current version works only in the Windows operating system. A free installation program and overview for Ox is available at www.doornik.com. A detailed installation guide for Ox is provided by MBBC, and is accessible without installing Ox. R is available at www.r-project.org/.
منابع مشابه
MBBC: Model-Based Bayesian Clustering
MBBC (Model-Based Bayesian Clustering) is developed to cluster longitudinal microarray data using a Bayesian objective function. This algorithm has advantages over conventional methods in that it clusters genes based on temporal changes of gene expressions and searches for the optimal number of clusters, as well as members of each cluster, without needing prior information. It is implemented us...
متن کاملEvaluation of the Performance of the Markov Blanket Bayesian Classifier Algorithm
The Markov Blanket Bayesian Classifier is a recentlyproposed algorithm for construction of probabilistic classifiers. This paper presents an empirical comparison of the MBBC algorithm with three other Bayesian classifiers: Naïve Bayes, Tree-Augmented Naïve Bayes and a general Bayesian network. All of these are implemented using the K2 framework of Cooper and Herskovits. The classifiers are comp...
متن کاملComparison of Four Classification Methods for Brain-computer Interface
This paper examines the performance of four classifiers for Brain Computer Interface (BCI) systems based on multichannel EEG recordings. The classifiers are designed to distinguish EEG patterns corresponding to performance of several mental tasks. The first one is the basic Bayesian classifier (BC) which exploits only interchannel covariance matrices corresponding to different mental tasks. The...
متن کاملGender-based Differences in Associations between Attitude and Self-esteem with Smoking Behavior among Adolescents: A Secondary Analysis Applying Bayesian Nonparametric Functional Latent Variable Model
Background: Different patterns of gender-based relationships between attitude toward smoking and self-esteem with smoking behavior have reported. However, such associations may be much more complex than a simply supposed linear relationship. We aimed to propose a method of providing hand details on the total and gender-based scenarios of the relationships between attitude toward smoking and sel...
متن کاملUncertainty Modeling of a Group Tourism Recommendation System Based on Pearson Similarity Criteria, Bayesian Network and Self-Organizing Map Clustering Algorithm
Group tourism is one of the most important tasks in tourist recommender systems. These systems, despite of the potential contradictions among the group's tastes, seek to provide joint suggestions to all members of the group, and propose recommendations that would allow the satisfaction of a group of users rather than individual user satisfaction. Another issue that has received less attention i...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Bioinformatics
دوره 24 6 شماره
صفحات -
تاریخ انتشار 2008