Mining host-pathogen interaction from biomedical literature
Abstract
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] With infectious diseases affecting humans, animals, and plants, the knowledge on mechanisms of infection is critical in designing drugs as well as developing therapeutic cures against pathogenic organisms. Our understanding of the mechanisms can be greatly enhanced by the data at the molecular level, at which interactions between the host and pathogen proteins occur. While conducting experiments to verify a biomedical discovery is costly in both time and resources, research community is overwhelmed by the amount of experimentally verified data collected in PubMed, the largest repository of biomedical literature. As a result, a method that automatically mines the precious information from PubMed and presents it in an easily accessible form is desired. Recently, there have been several databases collecting information on host-pathogen interactions, but they either curate the data manually, or gather data from other general protein-protein interaction sources. Realizing the need, PHILM-LB, a novel system that automatically mines host-pathogen protein-protein interaction data from the PubMed abstracts, is developed.
Degree
M.S.
Thesis Department
Rights
Access to files is limited to the University of Missouri--Columbia.