Tag: Boolean networks

Uncovering the “master switches” of biochemical networks can explain the effects of drugs in the destruction of cancer cells

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:

Luddy Press Release

Instituto Gulbenkian de Ciência Press Release

You can read the article here:


*Those interested in contacting the authors should do so directly, via the links provided above.… continue reading.

New Ph.D. Graduate

Congratulations to Alexander Gates for successfully defending his dissertation entitled “The anatomical and effective structure of complex systems” on April 3rd 2017, co-supervised by Randy beer and Luis Rocha. Alex completed a dual-PhD degree in the Complex Systems track of the Informatics PhD Program as well as the Cognitive Science program at Indiana University. Alex has accepted a postdoctoral position at Northeastern University at the Center for Complex Network Research. … continue reading.

Art-Science Installation Musical Morphogenesis

Musical Morphogenesis’ is an interactive installation that translates to sound, movement and lights the dynamics behind the development of petals in a flower. It is a collaborative piece developed by designers, architects, musicians and scientists in Luis Rocha‘s CASCI group. The control of this robotic “macroscope” is an implementation of the gene regulatory network of the Thaliana Arabidopsis flower. The installation provides a sensorial exploration of the dynamics between genes and proteins that leads to organ formation in plants, namely sepals, stamen, and petals. The genetic network provides an interactive “genetic soundtrack” that allows visitors to control the development of the plant towards its wild-type or mutant states. The installation has been on display at various museums such as the Science Museum in Lisbon, Gulbenkian Foundation, and the Belém ArtFest. This week it will be displayed at Dia D Ligações – Gulbenkian Foundation.… continue reading.

Control of Complex Networks

Network science has allowed us to understand the organization of complex systems across disciplines. However, there is a need to understand how to control them; for example, to identify strategies to revert a diseased cell to a healthy state in cancer treatment. Recent work in the field—based on linear control theory—suggests that the controllability of complex systems can be predicted solely from the graph of interactions between variables, without considering their dynamics. Such graph-based approaches have been used, for instance, to suggest that biological systems are harder to control and have appreciably different control profiles than social or technological systems. The methodology has also been increasingly used in many applications from financial to biochemical networks.

In work published today in Nature Scientific Reports, CNetS graduate student Alexander Gates and Professor Luis Rocha demonstrate that such graph-based methods fail to characterize controllability when dynamics are introduced. The study computed the control profiles of large ensembles of multivariate systems as well as existing Systems Biology models of biochemical regulation in various organisms.… continue reading.