Systems Biology and Algorithm Development Lab
The Systems Biology and Algorithm Development Lab is working to develop novel techniques towards the integration of high throughput data and biological knowledge to unravel mechanisms of interaction in biological systems. Its goals include the development of algorithms for prognosis and diagnosis, which take advantage of the intrinsic nature of the biological systems, and to provide TGen researchers with new computational tools to allow them to apply systematically the techniques developed by the Division. We hope that this work will position TGen as a center to validate genomic signal processing algorithms such as classification, clustering and network inference.
Current Projects:
1. Implementation and validation of multivariate SNP-based genome wide association algorithms.
2. Quantification of the limitations of feature selection and error estimation in high-throughput settings.
3. Integration of prior biological knowledge in the design of system models and diagnosis/prognosis classifiers.
4. Development of fusion techniques for integration of different data types in system models and classifiers.
Staff:
Edward R. Dougherty, Ph.D., Unit Head
|
E-MAIL THIS ARTICLE
PRINT THIS PAGE
Podcasts
NewsFeed