gene-disease associations

Knowledge-based methods in biomedicine

Robert Hoehndorf, Associate Professor, Computer Science

Aug 26, 12:00 - 13:00

B9 L2 H1

Biostatistics artificial intelligence gene-disease associations drug targets

The life sciences have invested significant resources in the development and application of semantic technologies to make research data accessible and interlinked, and to enable the integration and analysis of data. Utilizing the semantics associated with research data in data analysis approaches is often challenging. Now, novel methods are becoming available that combine symbolic methods and statistical methods in Artificial Intelligence. In my talk, I will describe how to apply knowledge-based methods for the analysis of biological and biomedical data, in particular identification of gene-disease associations and drug targets.

How much do model organism phenotypes contribute to the computational identification of human disease genes?

1 min read · Sun, Sep 4 2022

Ontologies phenotype ontologies gene-disease associations

PhD Student Sarah M Alghamdi from the Bio-Ontology Research Group (BORG) explains how phenotype ontologies help in identifying disease genes through phenotype comparison. Her research was picked as a highlight in the July 2022 issue of Disease Models and Mechanisms Journal.