Computational Cell Biology

Computational cell biology is the field of study that applies the mathematics of dynamical systems together with computer simulation techniques to the study of cellular processes. The field encompasses several topics that have been studied long enough to be well established in their own right such as calcium signaling, molecular motors and cell motility, the cell cycle, and gene expression during development. In addition to providing a recognizable larger community for topics such as these, this course will provide a base for the development of newer areas of inquiry – for example the dynamics of intracellular second-messenger signaling, of programmed cell death, of mitotic chromosome movements, and of synthetic gene networks. Unlike computational genomics or bioinformatics, computational cell biology is focused on simulation of the molecular machinery (genes-proteins-metabolites) that underlie the physiological behavior (input-output characteristics) of living cells.

The three week course in Computational Cell Biology will incorporate a series of didactic lectures on the mathematics of dynamical systems, computational simulation techniques, cell biology and molecular biology. Practicing theoreticians and experimentalists will rotate in for 1-3 day visits during the course to give lectures and interact with the students. Midway through the course, students will select an area for independent study, and the focus of the last week of the course will largely be on these projects, supplemented by continued visiting lecturers.

Visiting faculty will change from year to year, and the specific topics covered will vary. Potential areas include:

Fundamentals
-Cell biology (signaling, differentiation, motility, cell cycle,
apoptosis)
-Molecular biology (gene expression, posttranslational modification,
proteolysis)
-Mathematical biology (dynamical systems, phase plane, elementary
bifurcations)
-Computational tools (numerical simulation, software, SBML)

Advanced Topics
Sniffers, buzzers, toggles and blinkers
Practical bifurcation theory
Reaction-diffusion-advection
Stochastic modeling
Physical chemistry of aggregation/polymerization
Mechano-chemical dynamics
Sensitivity & robustness
Optimization, parameter estimation

Case Studies
calcium signaling
cancer modeling
cardiac modeling
signal transduction networks
gene expression
apoptosis
cell cycle regulation
cytoskeletal dynamics
neural models
intracellular trafficking & molecular motors
cell motility & chemotaxis
mechanics of mitosis & cell division
oscillations & bursting in neurosecretion
fertilization phenomena
development
mitochondrial function
cell differentiation
synthetic gene networks
circadian modeling
computational modeling in drug discovery
+ show speakers and program
Instructors:
Reka Albert, Pennsylvania State University
Leslie Loew, University of Connecticut Health Center
Gregory Smith, College of William and Mary

23 Jul - 12 Aug 2013
Cold Spring Harbor
United States of America
meeting website