Electronic Theses and Dissertations

Identifier

1156

Date

2014

Document Type

Thesis

Degree Name

Master of Science

Major

Bioinformatics

Committee Chair

Ramin Homayouni

Committee Member

Vasile Rus

Committee Member

Vinhthuy Phan

Abstract

Recent developments in high-throughput genomic technologies allow researchers to investigate gene expression levels and genetic variation associated with phenotypes and outcomes. However, understanding the mechanisms responsible for regulation of gene expression and identification of critical components in the regulatory pathways responsible for phenotypes and diseases remain challenging. This thesis proposes a novel method to identify genes which are likely to be regulated by a given transcription factor (TF) based on functional information extracted from the biomedical literature. Existing methods for finding potential targets of a transcription factor utilize laboratory approaches such as Chromatin Immunoprecipitation (ChIP). By mining the literature, we hypothesize that new gene targets for TFs may be identified by extracting hidden relationships among genes and TFs. In this thesis project an approach was developed that combines Natural Language Processing (NLP) and Literature Based Discovery (LBD) techniques. The approach was evaluated using a set of publicly available ChIP data.

Comments

Data is provided by the student.

Library Comment

Dissertation or thesis originally submitted to the local University of Memphis Electronic Theses & dissertation (ETD) Repository.

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