The Biomedical Knowledge Engineering group at ISI develops practical, knowledge-centric systems for biomedical researchers. We focus on finding the strategic information bottlenecks in the current biomedical informatics architecture and work with top-level computer scientists to create well-engineered solutions and infrastructure.

Our work broadly follows the model shown to the right.

We use the primary research literature as our primary source for scientific knowledge. We use text mining techniques to extract informaiton and assist the process of creating knowledge systems from the documents. This includes both unsupervised and supervised methods to perform large-scale analyses both across and within domains. Following this work, we are both developing and tailoring knowledge representation and reasoning technology in collaboration with members of the biomedical knowledge engineering community to develop the process of 'closing the loop' shown in the model: to construct a computational methodology for scientific reasoning in biomedicine.

Ultimately, we seek to transform the computational infrastructure supporting the scientific enterprise and specifically to accelerate methods of discovering and delivering improved medical treatment (i.e., 'translational research').

This is a very exciting and challenging field, requiring expertise from multiple fields and we are seeking partnerships with end users (both basic and medical scientists in academia and industry), government agencies, disease foundations, hospitals and the public.

If you have similar interests to us, or are interested in collaborating, please contact us.

We maintain an active TWiki describing all aspects of our work, if you'd like to dive into a little more detail.