Congratulations to Emilio Ferrara for winning the 2016 Junior Scientific Award from the Complex Systems Society (CCS), which unveiled the winners of the CSS scientific awards in a packed plenary session at ECCS’16 in Amsterdam, the Netherlands. Continue reading Emilio Ferrara receives Junior Scientific Award at CSS’16
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.
Recent CASCI Complex Systems & Networks Phd program graduate Artemy Kolchinsky, is now a postdoc at the Santa Fe Institute. While at SFI, Kolchinsky is working with “David Wolpert on several projects related to optimal use of information and prediction. One is the problem of modeling and analyzing complicated dynamical systems that require large amounts of time and computational power to simulate. […] Another project investigates connections
between information processing and statistical physics. […] The two are [also] beginning to work on understanding why different social groups develop different organizations, whether the group is a prehistoric tribe or a business firm.” More details on the SFI update newsletter.
Modularity in complex systems can be observed in networks and across dynamical states, time scales, and in response to different kinds of perturbations. In a paper published in Physical Review E (Rapid Communication), Kolchinsky, Gates & Rocha propose a principled alternative to detecting communities in static and dynamical networks. The method demonstrates that standard modularity measures on static networks can be seen as a special case of measuring the spread of perturbations in dynamical systems. Thus, the new method offers a powerful tool for exploring the modular organization of complex dynamical systems.
Congratulations to Artemy Kolchinsky a brand new PhD in 2015 in the Complex Systems track of the Informatics PhD Program. Artemy’s PhD Dissertation is entittled “Measuring Scales: Integration and Modularity in Complex Systems“.
Read new papers from CASCI on developing the mathematical toolbox available to deal with computing distances on weighted graphs, applying distance closures for computational fact checking, and computing multi-scale integration in brain networks:
T. Simas and L.M. Rocha .”Distance Closures on Complex Networks”. Network Science, doi:10.1017/nws.2015.11.
G.L. Ciampaglia, P. Shiralkar, L.M. Rocha, J. Bollen, F. Menczer, A. Flammini . “Computational fact checking from knowledge networks.” PLoS One. In Press. arXiv:1501.03471.
A. Kolchinsky, M. P. Van Den Heuvel, A. Griffa, P. Hagmann, L.M. Rocha, O. Sporns, J. Goni . “Multi-scale Integration and Predictability in Resting State Brain Activity”. Frontiers in Neuroinformatics, 8:66. doi: 10.3389/fninf.2014.00066.
Congratulations to Filippo Radicchi for winning the First Junior Scientific Award from the Complex Systems Society (CCS), which unveiled the winners of the first CSS scientific awards in a packed plenary session at ECCS’14 in Lucca, Italy. CSS also honored Prof. Eugene Stanley with the Senior Scientific Award, and Dr. Giovanna Miritello with a second Junior Scientific Award. Quoting the nomination:
Filippo Radicchi is among the best young researchers in complex systems and networks, with contributions that span from theoretical studies of structural and dynamical properties of networks to analyses of large-scale empirical data about human behaviour and performance.
We could not agree more.
Luis M. Rocha is Professor of Informatics and Cognitive Science at Indiana University, Bloomington, USA. He is director of the Complex Networks & Systems graduate Program in Informatics, member of the Indiana University Network Science Institute, and core faculty of the Cognitive Science Program at Indiana University, Bloomington, USA. Dr. Rocha is a Fulbright Scholar and is also Principal Investigator and the director of the Computational Biology Collaboratorium and in the Direction of PhD program in Computational Biology at the Instituto Gulbenkian da Ciencia, Portugal. His research is on complex networks & systems, Computational & Systems Biology, and Computational Intelligence and he is the Principal Investigator of the Complex Adaptive Systems & Computational Intelligence lab (CASCI). He received his Ph.D in Systems Science in 1997 from the State University of New York at Binghamton. From 1998 to 2004 he was a permanent staff scientist at the Los Alamos National Laboratory, where he founded and led a Complex Systems Modeling Team during 1998-2002, and was part of the Santa Fe Institute research community. He has organized major conferences such as the Tenth International Conference on the Simulation and Synthesis of Living Systems (Alife X) and the Ninth European Conference on Artificial Life (ECAL 2007). He has published many articles in scientific and technology journals, and has been the recipient of several scholarships and awards. At Indiana University, he has received the Indiana University, School of Informatics & Computing, Trustees Award for Teaching Excellence in 2006 and 2015 after developing the complex systems training program and syllabi for several courses. Additional information about Prof. Rocha’s research, academic and personal activities is available on his website. Contact Information:
In The USA:
Center for Complex Networks and Systems Research
School of Informatics & Computing
Indiana University, 919 E. 10th St
Bloomington IN, 47408, USA
Instituto Gulbenkian de Ciência
Rua da Quinta Grande, 6
Apartado 14, P-2781-901 Oeiras, Portugal
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 the evolutionary capabilities of natural 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.
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CNetS faculty manage informal research groups and labs of various size and scope, including faculty, graduate students, postdocs, and visitors. Given the interdisciplinary and collaborative nature of CNetS, many researchers belong to more than one group.
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