Finding Functional Gene Relationships Using the Semantic Gene Organizer (SGO)

Author

Kevin Erich Heinrich, University of Tennessee - Knoxville

Date of Award

8-2004

Degree Type

Thesis

Degree Name

Master of Science

Major

Computer Science

Major Professor

Michael W. Berry

Committee Members

Ramin Homayouni, Jens Gregor

Abstract

Understanding functional gene relationships is a major challenge in bioninformatics and computational biology. Currently, many approaches extract gene relationships via term co-occurrence models from the biomedical literature. Unfortunately, however, many genes that are experimentally identified to be related have not been previously studied together. As a result, many automated models fail to help researchers understand the nature of the relationships. In this work, the particular schema used tomine genomic data is called Latent
Semantic Indexing (LSI). LSI performs a singular-value decomposition (SVD) to produce a low-rank approximation of the data set. Effectively, it allows queries to be interpreted in a more concept-based space and can allow for gene relationships to be discovered that would ordinarily be overlooked by other models.

Recommended Citation

Heinrich, Kevin Erich, "Finding Functional Gene Relationships Using the Semantic Gene Organizer (SGO). " Master's Thesis, University of Tennessee, 2004.
https://trace.tennessee.edu/utk_gradthes/2566