Rapid development of genome-wide profiling technologies has made it possible to conduct integrative analysis on genomic data from multiple platforms. In this study, we develop a novel integrative Bayesian network approach to investigate the …
While individual studies have demonstrated that mRNA expressions are affected by both copy number aberrations and microRNAs, their integrative analysis has largely been ignored. In this article, we use high-dimensional regression techniques to …
We propose a method to integrate high-dimensional genomics datasets across multiple platforms with multiple correlated imaging outcomes. This framework uses a hierarchical model to integrate biological relationships across platforms to identify genes …
In order to better understand cancer as a complex disease with multiple genetic and epigenetic factors, it is vital to model the fundamental biological relationships among these alterations as well as their relationships with important clinical …
We propose methods to integrate data across several genomic platforms using a hierarchical Bayesian analysis framework that incorporates the biological relationships among the platforms to identify genes whose expression is related to clinical …
We present a statistical framework, hierarchical relevance vector machine (H-RVM), for improved prediction of scalar outcomes using interacting high-dimensional input covariates from different sources. We illustrate our methodology for integrating …
We present a novel cloud system based on DBMS technology, where data mining algorithms are offered as a service. A local DBMS connects to the cloud and the cloud system returns computed data mining models as small relational tables that are archived …
We propose methods to integrate data across several genomic platforms using a hierarchical Bayesian analysis framework that incorporates the biological relationships among the platforms to identify genes whose expression is related to clinical …
Analyzing data from multi-platform genomics experiments combined with patients' clinical outcomes helps us understand the complex biological processes that characterize a disease, as well as how these processes relate to the development of the …