Document Type
Thesis
Date of Award
Spring 5-31-2016
Degree Name
Master of Science in Bioinformatics - (M.S.)
Department
Computer Science
First Advisor
Jason T. L. Wang
Second Advisor
Usman W. Roshan
Third Advisor
Zhi Wei
Abstract
Gene regulatory network (GRN) is a collection of regulators that interact with each other in the cell to govern the gene expression levels of mRNA and proteins. These regulators can either be DNA, RNA, protein and their complex. Transcriptional gene regulation is an important mechanisms in which an in-depth study can lead to various practical applications, and a greater understanding of how organisms control their cellular behavior. One of the most widely studied organisms in gene regulatory networks are the Mycobacterium tuberculosis and Corynebacterium glutamicum ATCC 13032.
Gene co-expression networks are of biological interests due to co-expressed genes which are controlled by the same transcriptional regulatory programs, as well as, studying the functionality of genes in a system-level. Correlation networks are increasingly being used in research applications, especially in the field of bioinformatics. It facilitates networks based on gene screening methods which can be used to identify biomarkers or therapeutic targets. Computational methods use for the development of network models, as well as, the analysis of their functionality proved to be of valuable resources.
Recommended Citation
Somoza, Maria E., "Gene network understanding and analysis" (2016). Theses. 279.
https://digitalcommons.njit.edu/theses/279
