Author

Bryan Laraway

Date

9-2015

Document Type

Thesis

Degree Name

M.B.I.

Department

Department of Medical Informatics and Clinical Epidemiology

Institution

Oregon Health & Science University

Abstract

In the study of rare and undiagnosed diseases it is of critical importance to identify potential gene candidates for those disease in order to establish an appropriate treatment protocol. However, there may be insufficient resources available to investigate rare and undiagnosed diseases, so it may be necessary to identify potential gene candidates from patient clinical observations to narrow the focus of the investigation. Two approaches for identifying gene candidates are investigated and compared: the OWLSim package for comparing the semantic similarity of phenotypes and the Phenolog approach for identifying orthologous phenotypes by searching for orthologous gene enrichment between phenotypes.

In comparing the two approaches by measuring ranked-recall of known disease causative genes, the Phenolog approach performed better than the OWLSim package. However, each approach was able to exclusively identify known disease causative genes, indicating that a combined approach would provide a better retrieval of correct gene candidates than either method alone.

Identifier

doi:10.6083/M4Z60N1W

School

School of Medicine

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.