Karen Eilbeck, M.Sc., Ph.D.

Dr. Karen Eilbeck earned both her M.Sc. degree in Bioinformatics and her Ph.D. in Biochemistry at the University of Manchester in England. She did postdoctoral training in the Department of Computer Science at the University of Manchester. She is a Professor in the University of Utah’s Biomedical Informatics Department. Prior to moving to Utah, she was a scientist at Celera Genomics in Maryland, and at the Berkeley Drosophila Genome Project at U.C. Berkeley.

Dr. Eilbeck maintains an active lab where the main focus is knowledge representation for genomic data. She has mentored successful Ph.D. & MS students and post docs who have gone on to academic, government, and industry positions. Her expertise is in managing and accessing biological data in order to better understand diseases. Her research involves the annotation of biological sequences, in particular genome sequences. Genomic annotation is the process of adding further knowledge to the raw sequence data, such as the location of genes, the functions of the gene products, and the positions of known mutations. Her group maintains the Sequence Ontology, an open-source project for organizing and naming the parts of genomic sequence and the relationships between these parts. This project has unified the vocabulary used to annotate genomes, enabling computational exploration of data from many sources. It forms the terminology used by many genome software programs and model organism communities. She continues to work with the GA4GH standards development organization to build interoperability around biological data. Her group worked closely with the ClinGen Initiative where they developed ClinVar Miner – a tool for clinical genetics professionals to better understand ClinVar submissions.

More information about Dr. Eilbeck can be found at: http://eilbeck-lab.genetics.utah.edu/

Google Scholar: http://scholar.google.com/citations?hl=en&user=ccf6djEAAAAJ

Research Statement

Quality control of genomic annotations; Management and analysis of personal genomics data; Ontology development to structure biological, genomic and phenotypic data

Global Impact