Title
Integrative Gene Regulatory Network Inference Using Multi-omics Data
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Computer Science
Date of Award
Spring 2017
Abstract
Biological network inference is of importance inunderstanding the underlying biological mechanisms. Gene regulatory network describes molecular interactions of complex biological processes by using a graph model, where nodes and edges represent genes and their regulations respectively. In most research studies, the molecular interactions (edges) of the gene regulatory networks are inferred from a single type of genomic data, for example, gene expression data.
Advisor
Sang C. Suh
Subject Categories
Computer Sciences | Data Science | Physical Sciences and Mathematics
Recommended Citation
Zarayeneh, Neda, "Integrative Gene Regulatory Network Inference Using Multi-omics Data" (2017). Electronic Theses & Dissertations. 845.
https://digitalcommons.tamuc.edu/etd/845
