Date of Award
Master of Science
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.
dissertation or thesis originally submitted to the local University of Memphis Electronic Theses & dissertation (ETD) Repository.
Hasan, Sk Md Nahid, "Identifying TF Target Genes Using Natural Language Processing and Literature Based Discovery Approach" (2014). Electronic Theses and Dissertations. 972.