Genomics and health are prime areas for the development and application of novel intelligent algorithms due to a large amount of available research data, the high complexity of the problem, and the significant social and economic benefits of improving health outcomes in humans. In the past, genomics and health have been one of the key drivers in the development of Artificial Intelligence methods, including machine learning, expert systems, or graph-based algorithms. I will introduce the new seminar series on Artificial Intelligence for Genomics and Health (AI4GH), and then discuss our recent research on the use of knowledge graphs for the analysis of biological and biomedical data. I will focus on the identification of gene-disease associations and drug targets as well as the prediction of protein functions.
Robert Hoehndorf is an Assistant Professor in Computer Science at King Abdullah University of Science and Technology in Thuwal. His research focuses on the applications of knowledge-based algorithms in biology and biomedicine, with a particular emphasis on integrating and analyzing heterogeneous, multimodal data. Robert is an associate editor for the Journal of Biomedical Semantics, BMC Bioinformatics, Applied Ontology, PLoS ONE, and editorial board member of the journal Data Science. He published over 100 research papers in journals and international conferences.