Background: Microarray technology has unveiled transcriptomic differences among tumors of various phenotypes, and, especially, brought great progress in molecular understanding of...
Atsushi Niida, Andrew D. Smith, Seiya Imoto, Shuic...
Background: Identifying genes and pathways associated with diseases such as cancer has been a subject of considerable research in recent years in the area of bioinformatics and co...
Zhenqiu Liu, Ronald B. Gartenhaus, Ming Tan, Feng ...
Nonparametric Bayesian mixture models, in particular Dirichlet process (DP) mixture models, have shown great promise for density estimation and data clustering. Given the size of ...
Background: The completion of the sequencing of human, mouse and rat genomes and knowledge of cross-species gene homologies enables studies of differential gene expression in anim...
Hong Fang, Weida Tong, Roger Perkins, Leming M. Sh...
We discuss Bayesian methods for learning Bayesian networks when data sets are incomplete. In particular, we examine asymptotic approximations for the marginal likelihood of incomp...