Conveners
M3-1 Stochastic Biology (DPMB) I Biologie stochastique (DPMB)
- Andrew Rutenberg (Dalhousie University)
Many biological processes in cells are complex yet sparsely characterized. Constructing physical models of such systems then often requires making many assumptions based on guesswork. Instead of ignoring or guessing unknown details in complex processes we have derived universal balance relations to rigorously characterize stochastic fluctuations in incompletely specified systems. Specifying...
The development of drug resistance is a serious problem that reduces therapeutic susceptibility and complicates the treatment of infectious disease and cancer. To explore non-genetic causes of spontaneous drug resistance in rapidly proliferating cell populations, we constructed a set of synthetic transcriptional regulatory networks in yeast Saccharomyces cerevisiae to control the expression of...
Human aging leads to the stochastic accumulation of damage. We model an aging population using a stochastic network model. Individuals are modeled as a network of interacting nodes, representing health attributes. Nodes in the network stochastically damage and repair, with rates dependent on the state of their neighbors. Damaged nodes represent health deficits. Overall damage in the network is...
Dendrites are often excitable structures involved in the signal processing of almost all neurons.
We find that when an active dendrite has a greater intrinsic variability and a longer refractory period
than the soma, it will determine spike times for weak inputs but be entrained by somatic spikes for
strong inputs. This produces an input-dependent gating of dendritic noise. As a result,...
