Bringing networks to life.
From sub-cellular biology to the Internet, networks capture the architecture behind complex behavior. They map the pathways that channel genetic information between cellular components, spread viruses among linked individuals and help neuronal signals propagate between brain regions. But the network is just the static architecture underlying these rich dynamics. How does this structure translate into dynamic behavior?
At the Complex Network Dynamics lab we translate structure into function. Predicting how signals spread along network pathways, uncovering the network components that contribute to the system’s stability and resilience and detecting the nodes and links that enable information to flow throughout the system. Our ultimate goal is to systematically use complex network data to understand, predict and control its observed behavior.
So, what can your network do?
Evolving patterns of epidemic flow
While topology is static - the patterns of flow can change with time. Watch as the flow shifts with time from the hubs to the peripheral nodes. Read more
Signal propagation in complex networks
How does a signal travel in a network environment? Unpredictably. Here we use a dynamic metric to predict the actual spatio-temporal propagation patterns. Read more
Dr. Soumen Majhi
Dr. Aradhana Singh
Dr. Chandrakala Meena
Dr. Suman Acharyya
Dr. Adar HaCohen
Dr. Chittaranjan Hens
Dr. Priodyuti Pradhan
Dr. Nir Schreiber
Dr. Merav Stern
Dynamic patterns of information flow in complex networks, Nature Communications 8, 2181 (2017)
Dynamics of Complex Networks
Statistical physics is the theory of interacting particles, gases and liquids. Its way of thought, however, goes beyond the domain of material science. In a broader perspective it provides us with a bridge between the microscopic description of a system and its observed macroscopic behavior. With it we can track the way in which system-level phenomena emerge from the mechanistic description of the system’s interacting components. For instance how the blind interactions between pairs of magnetic spins lead to the seemingly cooperative phenomena of magnetism.
At CND we develop the statistical physics of complex systems: our interacting particles are not atoms or spins, but rather genes, proteins, animal species or humans. We track the way in which individual human interactions lead to the spread of ideas, perceptions and also diseases, or how biochemical reactions between proteins transfer information between cellular components. These systems defy many of the classic principles that are central to the way physics is traditionally done. The particles are self-driven and non-Newtonian, the interactions are nonlinear and the underlying geometry in random, highly irregular and non-localized. In two words – complex systems.
With these challenges at hand, we find that the dynamic behavior of these complex systems – social, biological or technological – can be predicted, analyzed and understood using the tools and way of thought of statistical physics.
To get a popular taste of our scientific research please visit the links below
From Neurons to Facebook - Presentation at Nitzozot
Universal Resilience Patterns in Complex Networks video
An interview with American Friends of Bar-Ilan University
Editing by Lonnie Ostrow
Interview with Medan&Even
Krav Mada in Galey Zahal
Webinar with US and UK Embassies
An interview with Channel 20
Xiyun Zhang, Zhongyuan Ruan, Muhua Zheng, Jie Zhou, Stefano Boccaletti and Baruch Barzel
Nature Communications 13, 6218
Xiyun Zhang, Gabriela Lobinska, Michal Feldman, Eddie Dekel, Martin A Nowak, Yitzhak Pilpel, Yonatan Pauzner, Baruch Barzel and Ady Pauzner
PLoS Computational Biology 18, e1010391
Kiriil Kovalenko, Irene Sendiña-Nadal, Nagi Khalil, Alex Dainiak, Daniil Musatov, Andrei M Raigorodskii, Karin Alfaro-Bittner, Baruch Barzel, Stefano Boccaletti
Communications Physics 4, 1
Yanjun Wang, Yakun Cao, Chenping Zhu, Fan Wu, Minghua Hu, Vu Duong, Michael Watkins, Baruch Barzel & H. Eugene Stanley.
Scientific Reports 10, 6890
Nir Lahav, Irene Sendiña Nadal, Chittaranjan Hens, Baruch Ksherim, Baruch Barzel, Reuven Cohen and Stefano Boccaletti
Physical Review E 98, 052204
Baruch Barzel, Ofer Biham, Raz Kupferman, Azi Lipshtat and Amir Zait
Physical Review E 82, 021117-28
Franck Le-Petit, Baruch Barzel, Ofer Biham, Evelyne Roueff and Jacques Le-Bourlot
Astronomy and Astrophysics 505, 1153-1165
Baruch Barzel and Ofer Biham
In Proceeding of the International Workshop on Molecules in Space & Laboratory, Paris, France, (May 14-18, 2007). Eds.: J.L. Lemaire and F. Combes, 425-430
Response to comment on Network link prediction by global silencing of indirect correlations
Baruch Barzel and Albert-László Barabási
Nature Biotechnology 33, 339-342
Response to comment on Binomial moment equations for stochastic reaction systems
Baruch Barzel and Ofer Biham
Physical Review Letters 112, 088902
Nework science and automation
Springer Handbook of Automation
Lorenzo Zino, Baruch Barzel and Alessandro Rizzo
Proceedings of the Third International Winter School and Conference on Network Science
Rami Puzis, Baruch Barzel and Erez Shmueli
Academic Press - Elsevier
Graph theory properties of cellular networks
Handbook of Systems Biology – Concepts and Insights, Chapter 9.
Baruch Barzel, Amitabh Sharma and Albert-László Barabási