Biological systems attain their functionality through the activity of multiple interacting elements, the distribution of which ranges over many orders of magnitude in both space and time. To a large extent, the means by which the functionality of these networks develops and evolves in relation to the environment is still a mystery. The Laboratory for Network Biology Research, comprising researchers from four Technion faculties (Medicine, Physics, Electrical Engineering and Chemical Engineering), aims at developing an experimental and theoretical framework for the study of biological networks, with particular emphasis on general mechanisms that allow for robust, yet adaptive, functionality in complex environments. Our research is centered on two experimental systems originating from different areas of biology, and on a theoretical effort to develop a universal approach to network biology, which, while aiming at basic principles, is cognizant of the particularities of specific systems.
The NBRL were set up in June 2007, and comprise researchers from different faculties, all located together in a single wing of Fishbach building. This cooperative setting of researchers from multiple disciplines working together in a single space is atypical of the Technion. The researchers in the center consist of the following individuals. Professors Erez Braun from Physics, Naama Brenner from Chemical Engineering, Omri Barak, Shimon Marom , Noam Ziv and Danny Eytan from Medicine, and Ron Meir and Daniel Soudry from Electrical Engineering.
Main Intrest areas : 1. Biophysical and functional aspects of bio-electricity in proteins, cells and networks, focusing on mechanisms underlying emergence, dynamics and adaptation of bioelectrical phenomena at extended timescales.2. Advancing a framework of relational physiology, focusing on the functional organization of systems that are embedded in a responsive and adaptive environment, implementing natural input statistics and closed-loop experimental designs.
Research interests include advanced patient monitoring and applied systems physiology. He focuses on combining tools from diverse fields such as machine learning and nonlinear dynamical systems to create better physiological models and improve prediction of disease and patient’s states and trajectories.
We are experimental group which studies the dynamics and turnover of synaptic molecules, the capacity of synapses to preserve their individual properties, the degree to which this capacity depends on activity and neuromodulators and the rules and principles that govern directed and spontaneous remodeling of excitatory and inhibitory synaptic specializations.
Main areas of interst : a quantitative understanding of intelligence, both artificial and biological — and in the possible relationship between the two. We focus on neural network models, which are a canonical model for neural computation in the brain and are a central part of many modern artificial intelligence systems.
Main Interst areas: Mulitple timescales & Nueronal representations. Using experimental results on multiple levels – behavioral, electrophysiological, imaging or any other available' we try to infer some concepts or clues about certain phenomena. We then use mathematical modeling to test whether it all makes sense, and hopefully gain some new insight. With this new insight I return to my experimental collaborators and try to grasp for the next piece in the puzzle.