CONTROLLING NETWORK DYNAMICS
نویسندگان
چکیده
منابع مشابه
Gene network dynamics controlling keratinocyte migration
Translation of large-scale data into a coherent model that allows one to simulate, predict and control cellular behavior is far from being resolved. Assuming that long-term cellular behavior is reflected in the gene expression kinetics, we infer a dynamic gene regulatory network from time-series measurements of DNA microarray data of hepatocyte growth factor-induced migration of primary human k...
متن کاملTemporal dynamics of a homeostatic pathway controlling neural network activity
Neurons use a variety of mechanisms to homeostatically regulate neural network activity in order to maintain firing in a bounded range. One such process involves the bi-directional modulation of excitatory synaptic drive in response to chronic changes in network activity. Down-scaling of excitatory synapses in response to high activity requires Arc-dependent endocytosis of glutamate receptors. ...
متن کاملControlling spin-spin network dynamics by repeated projective measurements.
We show that coupled-spin network manipulations can be made highly effective by repeated projections of the evolving quantum states onto diagonal density-matrix states (populations). As opposed to the intricately crafted pulse trains that are often used to fine-tune a complex network's evolution, the strategy hereby presented derives from the "quantum Zeno effect" and provides a highly robust r...
متن کاملMicrotubule dynamics: Controlling split ends
The rapid switching between growth and shrinkage at microtubule ends is important for many cellular processes. Recent studies on the structure of the microtubule and on the mechanism of action of the microtubule regulators XKCM1 and OP18 have revealed how these switching events are regulated.
متن کاملControlling on-off intermittent dynamics.
On-off intermittent chaotic behavior occurs in physical systems with symmetry. The phenomenon refers to the situation where one or more physical variables exhibit two distinct states in their time evolution. One is the ‘‘off’’ state where the physical variables remain constant, and the other is the ‘‘on’’ state where the variables temporarily burst out of the ‘‘off’’ state. We demonstrate that ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Advances in Complex Systems
سال: 2019
ISSN: 0219-5259,1793-6802
DOI: 10.1142/s0219525919500218