Traditionally, disease classifications have focused on characterizing diseases based on sets of related symptoms/phenotypes. However, as our understanding of genetic contributions to disease susceptibility and progression evolves, we start noticing that diseases with similar symptoms may have completely different causes. As genetic data becomes more highly available, it becomes possible to classify diseases based on their genetic causative drivers instead of their phenotypes. In this study, we have (1) explored the relationship between 10 autoimmune diseases along with type II diabetes based on their genetic susceptibility information and compared such classifications to existing disease categorizations based on disease symptoms/phenotypes from Human Phenotype Ontology, NCI-thesaurus and the Disease Ontology, and (2) developed automated scripts to compute similarities and cluster diseases based on the specified criteria. Categorization based on genetic susceptibility can help identify diseases that share similar drug targets and benefit from similar diagnosis technologies. We hope to further develop our system to apply it to more disease categories.

Speaker Bios

Jia Tao is an assistant professor of Computer Science at The College of New Jersey. She has broad interest in different areas in Computer Science. She has done research in the areas of multilevel security databases, semantics for Object-Oriented programming languages, game theory and artificial intelligence. In the past several years, her research has focused on Knowledge Representation and Reasoning. She is particularly interested in using logical approaches to model real world phenomena, such as secrecy/privacy preserving reasoning and budget-constrained knowledge. She is also interested in health informatics and data analysis.

Leqi Liu is an undergraduate student at Bryn Mawr College. She is majoring in Computer Science and Mathematics. Her interests lie in Mathematical Analysis, Statistics, Logic and many subfields under Artificial Intelligence. Currently, she is doing research on health informatics focusing on disease classification and image processing for automating image analysis in biology experiment.