Knowledge-based Methods in Bioinformatics
Overview
My research develops knowledge-based methods for analyzing biological data and supporting scientific discovery. I build ontologies and knowledge bases that formalize biological concepts and relations, develop tools for constructing and analyzing these resources, and design computational methods that use their logical content in bioinformatics.
I will present how this work has progressed from representing biological knowledge to using it for inference and prediction. A central theme is preserving the meaning of formal knowledge when combining it with data-driven methods: representing logical definitions, incorporating deductive consequences, and using background knowledge to infer properties for which direct observations are unavailable. I will show how these contributions support protein function prediction, connect molecular changes to phenotypes, and identify candidate causes of rare diseases. This work demonstrates how knowledge representation and reasoning can turn accumulated biological knowledge into a computational resource for discovery.
Presenters
Brief Biography
Robert Hoehndorf is an Associate Professor of Computer Science at King Abdullah University of Science and Technology (KAUST), where he is the principal investigator of the Bio-Ontology Research Group (BORG).
Before joining the University in the fall of 2014, Professor Hoehndorf obtained his Ph.D. in Computer Science from the University of Leipzig, Germany, in 2009. Post-graduation, he spent several years in the U.K. as a research fellow and a research associate at Aberystwyth University and the University of Cambridge, respectively. He was also a postdoctoral fellow at the European Bioinformatics Institute, U.K.