Tag Archives: Boolean networks

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.

Control of Complex Networks

Control of the eukaryotic cell cycle of budding yeast Saccharomyces cerevisiae (from Nature.com, click for details)

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.

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Complex Adaptive Systems and Computational Intelligence

The Complex Adaptive Systems and Computational Intelligence (CASCI) group at Indiana University and the Instituto Gulbenkian de Ciencia works on complex networks & systems and their applications to informatics, biology, health, and social systems. We are particularly interested in the informational properties of natural and artificial systems which enable them to adapt and evolve. This means both understanding how information is fundamental for controlling the behavior and evolutionary capabilities of complex systems, as well as abstracting principles from natural systems to produce adaptive information technology.

Our research projects are on complex networks & systems, computational and systems biology, and computational intelligence; all our publications are available online as are news about our group. Additional information available on Luis Rocha’s Website and our group page at the Instituto Gulbenkian de Ciencia.

See our current roster and information on how to join our group. As a group, we are seriously interconnected with other research groups and networks: The Center for Complex Networks and Systems (CNets), the Indiana University Network Science Institute, the Cognitive Science Program, the FLAD Computational Biology Collaboratorium, the Instituto Gulbenkian de Ciência, and the Champalimaud Neuroscience Program.

You are welcome to join our mailing list CASCI-L by sending an email message to list@list.indiana.edu from the address you want to subscribe to the list, with subject line: subscribe CASCI-L Firstname Lastname (leave the message body blank.) More detailed instructions are available.