Contributions to Statistical Problems Related to Microarray Data

Microarray is a high throughput technology to measure the gene expression. Analysis of microarray data brings many interesting and challenging problems. This thesis consists three studies related to microarray data. First, we propose a Bayesian model for microarray data and use Bayes Factors to identify differentially expressed genes. Second, we study the cellular differentiation process and proposed a statistical test for detecting early differentiation genes. Third, we further proposed a model-based method for the cellular differentiation problem.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Statistics

Grantor

University of Illinois at Urbana-Champaign

Date dc:date

10000-01-01

Author dc:creator

• Hong, Feng

Contributors dc:contributor

• He, Xuming

• Statistics

Identifier

(UMI)AAI3392071

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/72582