Wednesday, June 15, 2016, at 12pm noon ET
Elucidating disease and dysfunction requires understanding how genotypic variation relates to phenotypic outcomes. Researchers produce data that are collated to generate hypotheses and novel discoveries, which feed into the clinic, further driving basic research. It is a beautiful cycle, but not all data is created equal along the way, and this process can take years.
Data integration is a key challenge as phenotype data is largely unstructured and is encoded in a variety of formats. Structuring phenotype data using ontologies assists in its algorithmic use to shed new light on how biological systems function across time and scale. The use of cross-species anatomy and phenotype ontologies can be combined with genomic analysis to support disease diagnosis, prognosis, and treatment selection. In this webinar, we explored the basics of what constitutes a quality ontology; when and how to apply the use of ontologies for biomedicine; how to reuse and integrate with other efforts; and how to build ontologies fit for this purpose. We discussed disease diagnostics and the emergent PTSD ontology for patient classification as exemplars.
About Melissa Haendel, PhD
Associate Professor in the Library and the Department of Medical Informatics & Clinical Epidemiology at Oregon Health & Science University
Dr. Melissa Haendel holds a Ph.D. in Neuroscience from the University of Wisconsin and completed postdoctoral training at the University of Oregon and Oregon State University. Currently, Dr. Haendel is Associate Professor in the Library and the Department of Medical Informatics & Clinical Epidemiology at the Oregon Health & Science University (OHSU), where she directs the Ontology Development Group. She is the principal investigator of the Monarch Initiative and is an active researcher in ontologies and data standards. Dr. Haendel is known for her work on biomedical resource discovery, open science, and reproducibility, and for her work on anatomy, cell, and phenotype ontologies, such as Uberon and the Human Phenotype Ontology.