Big data, ontologies, and the phenotypic bottle neck in epilepsy research

Unconnected data. Within the field of biomedicine, large datasets are increasingly emerging. These datasets include the genomic, imaging, and EEG datasets that we are somewhat familiar with, but also many large unstructured datasets, including data from biomonitors, wearables, and the electronic medical records (EMR). It appears that the abundance of these datasets makes the promise of precision medicine tangible – achieving an individualized treatment that is based on data, synthesizing available information across various domains for medical decision-making. In a recent review in the New England Journal of Medicine, Haendel and collaborators discuss the need in the biomedical field to focus on the development of terminologies and ontologies such as the Human Phenotype Ontology (HPO) that help put data into context. This review is a perfect segue to introduce the increasing focus on computational phenotypes within our group in order to overcome the phenotypic bottleneck in epilepsy genetics. Continue reading