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A HMM Approach to Identifying Distinct DNA Methylation Patterns for Subtypes of Breast Cancers

Xu, Maoxiong
http://rave.ohiolink.edu/etdc/view?acc_num=osu1305829056

Abstract Details

2011, Master of Science, Ohio State University, Computer Science and Engineering.
The United States has the highest annual incidence rates of breast cancer in the world; 128.6 per 100,000 in whites and 112.6 per 100,000 among African Americans. It is the second-most common cancer (after skin cancer) and the second-most common cause of cancer death (after lung cancer). Recent studies have demonstrated that hyper-methylation of CpG islands may be implicated in tumor genesis, acting as a mechanism to inactivate specific gene expression of a diverse array of genes (Baylin et al., 2001). Genes have been reported to be regulated by CpG hyper-methylation, include tumor suppressor genes, cell cycle related genes, DNA mismatch repair genes, hormone receptors and tissue or cell adhesion molecules (Yan et al., 2001). Usually, breast cancer cells may or may not have three important receptors: estrogen receptor (ER), progesterone receptor (PR), and HER2. So we will consider the ER, PR and HER2 while dealing with the data. In this thesis, we first use Hidden Markov Model (HMM) to train the methylation data from both breast cancer cells and other cancer cells. Also we did hierarchy clustering to the gene expression data for the breast cancer cells and based on the clustering results, we get the methylation distribution in each cluster. Finally, we correlate the HMM training results with the methylation distribution and get the biology meanings for the states in the HMM results.
Victor Jin, X (Advisor)
Raghu Machiraju (Committee Member)
85 p.
Bioinformatics; Computer Science
Breast Cancer; DNA methylation; Gene Expression; Hidden Markov Model

Recommended Citations

Citations

  • Xu, M. (2011). A HMM Approach to Identifying Distinct DNA Methylation Patterns for Subtypes of Breast Cancers [Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1305829056

    APA Style (7th edition)

  • Xu, Maoxiong. A HMM Approach to Identifying Distinct DNA Methylation Patterns for Subtypes of Breast Cancers. 2011. Ohio State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1305829056.

    MLA Style (8th edition)

  • Xu, Maoxiong. "A HMM Approach to Identifying Distinct DNA Methylation Patterns for Subtypes of Breast Cancers." Master's thesis, Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1305829056

    Chicago Manual of Style (17th edition)

osu1305829056
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© 2011, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.
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