Researchers from our lab, in collaboration with the Luddy School of Informatics, Computing, and Engineering, the Instituto Gulbenkian de Ciência, and Northeastern University have developed a mathematical framework that increases our ability to explain and control biochemical systems, including those involved in disease.
In a paper featured on the cover of the journal Proceedings of the National Academy of Sciences (PNAS), Professor of Informatics Luis Rocha and Alexander Gates (who earned his Ph.D. in complex networks and systems from the Luddy School), introduce an effective graph that can capture nonlinear logical redundancy present in biochemical network regulation, signaling, and control.
Rion Correia (a member of the CSBC lab, who also earned his Ph.D. in complex networks and systems from the Luddy School and Xuan Wang, a current Ph.D. candidate, and member of the lab) are also working on the project. Together, the authors demonstrate the utility of the approach with computational models of human cancer cells, showing that the effective graph reveals why some cancer medications are more effective than others in killing breast cancer cells.
You can read the full details via the press releases below:
You can read the article here:
*Those interested in contacting the authors should do so directly, via the links provided above.