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Identify Condition Specific Gene Co-expression Networks

Kalluru, Vikram Gajanan
http://rave.ohiolink.edu/etdc/view?acc_num=osu1338304258

Abstract Details

2012, Master of Science, Ohio State University, Electrical and Computer Engineering.
Since co-expressed genes often are co-regulated by a group of transcription factors, different conditions (e.g., disease versus normal) may lead to different transcription factor activities and therefore different co-expression relationships. A method for identifying condition specific co-expression networks by combining the recently developed network quasi-clique mining algorithm and the Expected Conditional F-statistic has been proposed. This method has been applied to compare the transcriptional programs between the non-basal and basal types of breast cancers. This work is a translational bioinformatics study integrating network analysis which lifts the traditional gene list based disease biomarker discovery to the gene and protein interaction level. This work presents a method for identifying condition specific gene co-expression networks. The method involves construction of a Weighted Graph Co-expression Network (WGCN) and mining the WGCNs to identify dense co-expression networks followed by a chi-square test based enrichment analysis for detecting condition specific co-expression relationship. The expression values in all the conditions for the genes constituting a condition specific co-expression network are visualized as heat maps which suggest that the genes are highly correlated in a specific condition but the correlations are disrupted in other conditions.
Kun Huang, PhD (Advisor)
Raghu Machiraju, PhD (Committee Member)
42 p.
Bioinformatics; Computer Engineering; Computer Science; Engineering
gene coexpression; bioinformatics; differential gene coexpression networks; systems biology; basal breast cancer; non-basal breast cancer

Recommended Citations

Citations

  • Kalluru, V. G. (2012). Identify Condition Specific Gene Co-expression Networks [Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1338304258

    APA Style (7th edition)

  • Kalluru, Vikram Gajanan. Identify Condition Specific Gene Co-expression Networks. 2012. Ohio State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1338304258.

    MLA Style (8th edition)

  • Kalluru, Vikram Gajanan. "Identify Condition Specific Gene Co-expression Networks." Master's thesis, Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1338304258

    Chicago Manual of Style (17th edition)

osu1338304258
1,297
© 2012, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.